System

Abstract

To provide a system.SOLUTION: A system includes: means for objectively determining an individual's strength; means for reading a determination result by the determining means into a natural language processing tool; means for allowing the natural language processing tool to output a concrete action proposal on the basis of the determination result; means for collecting data inputted by a user; means for pre-processing data collected by the collection means; means for extracting features from the data pre-processed by the processing means; means for analyzing the user's strength on the basis of the features extracted by the means for extracting features; means for generating a report on the basis of an analysis result by the analysis means; and means for distributing the report generated by the generation means to the user.SELECTED DRAWING: Figure 1

Description

[Technical field]

[0001] The technology of the present disclosure relates to a system. [Background technology]

[0002] Patent document 1 discloses a persona chatbot control method performed by at least one processor, the method including the steps of receiving a user utterance, adding the user utterance to a prompt including a description and related instruction sentence regarding the chatbot character, encoding the prompt, and inputting the encoded prompt into a language model to generate a chatbot utterance in response to the user utterance. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] JP 2022-180282 A Summary of the Invention [Problem to be solved by the invention]

[0004] Objectively assessing an individual's strengths and using the results to propose specific actions is important for individual ability development and human resource development. However, interpreting the results appropriately and linking them to specific actions requires specialized knowledge and experience, and it is also difficult to use the results in management. [Means for solving the problem]

[0005] The present invention provides a means for objectively judging the strengths of individuals, a means for inputting the judgment results into a natural language processing tool, and a means for the natural language processing tool to output specific action proposals based on the judgment results. This makes it possible to efficiently develop individual capabilities and cultivate human resources, and also makes it easy to utilize the results in management. [Brief description of the drawings]

[0006] [Figure 1] 1 is a conceptual diagram showing an example of the configuration of a data processing system according to a first embodiment. [Diagram 2] 1 is a conceptual diagram showing an example of main functions of a data processing device and a smart device according to a first embodiment. FIG. [Diagram 3] FIG. 11 is a conceptual diagram showing an example of the configuration of a data processing system according to a second embodiment. [Figure 4] FIG. 11 is a conceptual diagram showing an example of main functions of a data processing device and smart glasses according to a second embodiment. [Diagram 5] FIG. 13 is a conceptual diagram showing an example of the configuration of a data processing system according to a third embodiment. [Figure 6] FIG. 11 is a conceptual diagram showing an example of main functions of a data processing device and a headset-type terminal according to a third embodiment. [Figure 7] FIG. 13 is a conceptual diagram showing an example of the configuration of a data processing system according to a fourth embodiment. [Figure 8] FIG. 13 is a conceptual diagram showing an example of main functions of a data processing device and a robot according to a fourth embodiment. [Figure 9] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 10] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 11] FIG. 2 is a sequence diagram showing a process flow of the data processing system in the first embodiment of the first form example. [Figure 12] FIG. 11 is a sequence diagram showing a process flow of the data processing system in the application example 1 of the first embodiment. [Figure 13] FIG. 11 is a sequence diagram showing a process flow of the data processing system in the second embodiment of the second embodiment. [Figure 14] FIG. 13 is a sequence diagram showing a process flow of the data processing system in application example 2 of embodiment 2. [Figure 15] FIG. 13 is a sequence diagram showing a process flow of a data processing system in a third embodiment of the present invention. [Figure 16] FIG. 13 is a sequence diagram showing a process flow of the data processing system in the third application example of the third embodiment. [Figure 17] FIG. 13 is a sequence diagram showing the flow of processing in the data processing system in the first embodiment of the first form example when an emotion engine is combined. [Figure 18] FIG. 13 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1 of Form Example 1 when combined with an emotion engine. [Figure 19] FIG. 13 is a sequence diagram showing the flow of processing in the data processing system according to the embodiment 2 of the second embodiment in the case where an emotion engine is combined. [Figure 20] FIG. 13 is a sequence diagram showing the flow of processing in the data processing system in Application Example 2 of Form Example 2 when combined with an emotion engine. [Figure 21] FIG. 13 is a sequence diagram showing the flow of processing in the data processing system in the embodiment 3 of the form example 3 in the case where an emotion engine is combined. [Figure 22] FIG. 13 is a sequence diagram showing the flow of processing in the data processing system in Application Example 3 of Form Example 3 when combined with an emotion engine. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0007] Hereinafter, an example of an embodiment of a system according to the technology of the present disclosure will be described with reference to the accompanying drawings.

[0008] First, the terms used in the following description will be explained.

[0009] In the following embodiments, a signed processor (hereinafter simply referred to as a "processor") may be one arithmetic device or a combination of multiple arithmetic devices. Furthermore, a processor may be one type of arithmetic device or a combination of multiple types of arithmetic devices. Examples of arithmetic devices include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), an APU (Accelerated Processing Unit), or a TPU (TENSOR PROCESSING UNIT (registered trademark)).

[0010] In the following embodiments, a signed RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a working memory by the processor.

[0011] In the following embodiments, the coded storage is one or more non-volatile storage devices that store various programs, various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), and magnetic tapes.

[0012] In the following embodiments, a communication I / F (Interface) with a code is an interface including a communication processor and an antenna. The communication I / F controls communication between multiple computers. An example of a communication standard applied to the communication I / F is a wireless communication standard including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), Bluetooth (registered trademark), etc.

[0013] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." In other words, "A and / or B" means that it may be only A, only B, or a combination of A and B. In addition, in this specification, the same idea as "A and / or B" is also applied when three or more things are expressed by connecting them with "and / or."

[0014] [First embodiment]

[0015] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0016] 1, a data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0017] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a wide area network (WAN) and / or a local area network (LAN).

[0018] The smart device 14 includes a computer 36, a reception device 38, an output device 40, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The reception device 38, the output device 40, and the camera 42 are also connected to the bus 52.

[0019] The reception device 38 includes a touch panel 38A and a microphone 38B, and receives user input. The touch panel 38A detects contact with a pointer (e.g., a pen or a finger) to receive user input by the touch of the pointer. The microphone 38B detects the user's voice to receive user input by voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0020] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form of expression that the user 20 can perceive (e.g., voice and / or text). The display 40A displays visible information such as text and images according to instructions from the processor 46. The speaker 40B outputs voice according to instructions from the processor 46. The camera 42 is a compact digital camera equipped with an optical system including a lens, an aperture, and a shutter, and an imaging element such as a Complementary Metal-Oxide-Semiconductor (CMOS) image sensor or a Charge Coupled Device (CCD) image sensor.

[0021] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for transmitting and receiving various types of information between the processor 46 and the processor 28 via the network 54.

[0022] FIG. 2 shows an example of main functions of the data processing device 12 and the smart device 14.

[0023] As shown in Fig. 2, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32. The specific process program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific process program 56 from the storage 32, and executes the read specific process program 56 on the RAM 30. The specific process is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific process program 56 executed on the RAM 30.

[0024] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0025] In the smart device 14, the processor 46 performs the reception output processing. The storage 50 stores a reception output program 60. The reception output program 60 is used together with the specific processing program 56 by the data processing system 10. The processor 46 reads out the reception output program 60 from the storage 50, and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0026] Next, the specific processing by the specific processing unit 290 of the data processing device 12 will be described.

[0027] "Example 1"

[0028] In one embodiment of the present invention, a strengths judgment tool is used as a tool for objectively judging the strengths of an individual. This strengths judgment tool analyzes an individual's behavioral tendencies and thought patterns, and outputs the results as a report. The report is in text format, and its contents can be analyzed by a natural language processing tool.

[0029] "Example 2"

[0030] Next, the natural language processing tool reads the report output from the strengths assessment tool. The natural language processing tool analyzes the contents of the report and generates specific action suggestions based on the results. Specifically, based on the contents of the report, it suggests what actions an individual should take to make the most of their strengths.

[0031] "Example 3"

[0032] In addition, the natural language processing tool generates specific action suggestions to utilize the results of the strengths assessment tool for management. For example, if an individual's strength is "strategic thinking," it will suggest that the individual be involved in strategic planning and business planning. This will enable management to allocate personnel in a way that makes the most of each individual's strengths.

[0033] The process flow of each embodiment will be described below.

[0034] "Example 1"

[0035] Step 1: Each individual uses a strengths assessment tool to determine their own strengths. This tool analyzes the individual's behavioral tendencies and thought patterns, and outputs the results in a report.

[0036] Step 2: A natural language processing tool reads the report output from the strengths assessment tool. The tool analyzes the contents of the report and generates specific action suggestions based on the results.

[0037] "Example 2"

[0038] Step 1: Each individual uses a strengths assessment tool to determine their own strengths. This tool analyzes the individual's behavioral tendencies and thought patterns, and outputs the results in a report.

[0039] Step 2: A natural language processing tool reads the report output from the strengths assessment tool. The tool analyzes the contents of the report and generates specific action suggestions based on the results.

[0040] Step 3: The natural language processing tool also generates specific action suggestions to utilize the results of the strengths assessment tool in management. For example, if an individual's strength is "strategic thinking," it is suggested that the individual be involved in strategic planning and business planning. "Form example 3"

[0041] Step 1: Each individual uses a strengths assessment tool to determine their own strengths. This tool analyzes the individual's behavioral tendencies and thought patterns, and outputs the results in a report.

[0042] Step 2: A natural language processing tool reads the report output from the strengths assessment tool. The tool analyzes the contents of the report and generates specific action suggestions based on the results.

[0043] Step 3: The natural language processing tool also generates specific action suggestions to utilize the results of the strengths assessment tool for management. For example, if an individual's strength is "strategic thinking," it suggests involving the individual in strategic planning and business planning.

[0044] Example 1

[0045] Next, a description will be given of Example 1 of the embodiment 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal".

[0046] Conventional systems for assessing individual strengths often relied on subjective evaluations, making it difficult to make objective judgments. In addition, the results of the assessments could not be linked to specific action proposals, making it difficult to utilize the systems for personal self-improvement and management. Furthermore, there was also an issue of inconsistency in the process from data collection to report generation, making it difficult to operate efficiently.

[0047] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0048] In this invention, the server includes a means for objectively judging the strengths of an individual, a means for loading the judgment result into a natural language processing tool, a means for the natural language processing tool to output a specific action proposal based on the judgment result, a means for collecting data input by a user, a means for preprocessing the collected data, a means for extracting features from the preprocessed data, a means for analyzing the strengths of an individual based on the extracted features, a means for generating a report of the analysis result, and a means for delivering the generated report to a user. This makes it possible to objectively judge the strengths of an individual and to propose a specific action based on the result. In addition, since the process from collecting data to generating the report is performed consistently, efficient operation is possible.

[0049] "Means for objectively assessing an individual's strengths" is a method for analyzing an individual's behavioral tendencies and thought patterns, eliminating subjective elements, and objectively evaluating strengths.

[0050] A "natural language processing tool" is software for analyzing text data and extracting meaning, emotions, keywords, etc.

[0051] "Means for outputting specific action suggestions" refers to a method for presenting specific actions or improvement measures that an individual should take based on the analysis results.

[0052] The "means for collecting data input by the user" refers to a method for collecting data such as self-assessments and behavioral records provided by the user.

[0053] "Means for pre-processing collected data" refers to a method for removing unnecessary information from collected data and converting the data into a form suitable for analysis.

[0054] A "means for extracting features from preprocessed data" is a method for finding important keywords and patterns from the preprocessed data.

[0055] The "means for analyzing the strengths of an individual based on the extracted characteristics" is a method for evaluating and analyzing the strengths of an individual using the extracted characteristics.

[0056] "Means for generating a report based on the analysis results" refers to a method for compiling the analysis results and outputting them as a text-format report.

[0057] The "means for delivering the generated report to the user" refers to a method for transmitting the generated report to the user's terminal so that the user can check it.

[0058] The present invention is a system for objectively determining the strengths of an individual and proposing specific actions based on the results. A specific embodiment of this system will be described below.

[0059] System Configuration

[0060] Hardware and Software

[0061] This system consists of three main components: a server, a terminal, and a user. The server collects data, pre-processes it, extracts features, analyzes strengths, and generates and distributes reports. The terminal inputs data from users and receives reports. Users input data such as self-evaluations and behavioral records.

[0062] The server uses the following software:

[0063] Natural language processing tools: NLTK, spaCy

[0064] Machine learning model: scikit-learn, TENSORFLOW (registered trademark)

[0065] Program Processing

[0066] Data collection

[0067] The user inputs self-evaluation and behavior records from the terminal. For example, the user inputs a prompt sentence such as "I am good at working in a team and often demonstrate leadership." The terminal transmits this input data to the server.

[0068] Data Preprocessing

[0069] The server converts the received data into text format and filters out unnecessary information. Specifically, it removes HTML tags and special characters to make the text clean. For example, I am good at working in a team and often demonstrate leadership skills. " Remove HTML tags from the data.

[0070] Feature Extraction

[0071] The server uses natural language processing tools (e.g., NLTK and spaCy) to extract features from text data. Specifically, it performs keyword extraction and sentiment analysis. For example, it extracts keywords such as "teamwork," "leadership," and "problem-solving ability."

[0072] Strengths Analysis

[0073] The server analyzes the individual's strengths based on the extracted features. Here, a machine learning model (e.g., scikit-learn or TensorFlow) is used. For example, to determine that "leadership is a strength," the server calculates a score by comparing it with past data.

[0074] Generate reports

[0075] The server generates a report based on the analysis results and outputs it in text format. Specifically, it generates a report with the content such as "Your strengths are leadership and problem-solving ability."

[0076] Report distribution

[0077] The server sends the generated report to the user's terminal. The user can check the report on the terminal. For example, the user can receive a report such as "Your strengths are leadership and problem-solving ability" and can objectively understand his or her strengths.

[0078] Examples

[0079] When a user enters self-assessment data, a prompt sentence like the following is input to the generative AI model.

[0080] Example prompt:

[0081] "I work well in teams and often demonstrate leadership skills. I am also a good problem solver and enjoy tackling complex challenges."

[0082] Based on this prompt, the server collects data, pre-processes it, extracts features, analyzes strengths, and generates and distributes reports, allowing users to objectively evaluate their strengths and receive specific suggestions for action based on the results.

[0083] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0084] Step 1: Data collection

[0085] The user inputs self-evaluation and behavior records from the terminal. For example, the user inputs a prompt sentence such as "I am good at working in a team and often demonstrate leadership." The terminal sends this input data to the server. The input data is in text format, and the server receives it.

[0086] Step 2: Data Preprocessing

[0087] The server preprocesses the received text data. Specifically, it removes HTML tags and special characters to make the text clean. For example, I am good at working in a team and often demonstrate leadership skills. " HTML tags are removed from the data. The preprocessed text data is output.

[0088] Step 3: Feature Extraction

[0089] The server extracts features from the preprocessed text data. It uses natural language processing tools (e.g., NLTK and spaCy) to extract keywords and perform sentiment analysis. For example, it extracts keywords such as "teamwork," "leadership," and "problem-solving ability." The extracted feature data is output.

[0090] Step 4: Strengths analysis

[0091] The server analyzes the strengths of individuals based on the extracted feature data. Using a machine learning model (e.g., scikit-learn or TensorFlow), it compares the data with past data and calculates a score. For example, to determine that "leadership is a strength," the feature data is input into the model and a score is calculated. The analysis results are then output.

[0092] Step 5: Generate reports

[0093] The server generates a report based on the analysis results. It creates a text report with the content such as "Your strengths are leadership and problem-solving ability." The generated report is output.

[0094] Step 6: Report distribution

[0095] The server sends the generated report to the user's terminal. The user can check the report on the terminal. For example, the user can receive a report such as "Your strengths are leadership and problem-solving ability" and can objectively understand his or her strengths.

[0096] (Application example 1)

[0097] Next, a description will be given of Application Example 1 of Form Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0098] In conventional factories, it was difficult to assign workers to tasks that fully utilize their strengths, making it difficult to achieve efficient work allocation. In addition, there was a lack of means to objectively evaluate the behavioral tendencies and thought patterns of each worker and to assign them optimal tasks based on that. This led to problems of reduced work efficiency and reduced motivation among workers.

[0099] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0100] In this invention, the server includes a means for objectively judging the strengths of individuals, a means for inputting the judgment result into a natural language processing tool, a means for the natural language processing tool to output a specific action proposal based on the judgment result, and a means for allocating workers to optimal tasks based on the action proposal, thereby enabling efficient task allocation that makes the most of the strengths of workers.

[0101] "Individual strengths" are the specific abilities and characteristics that each worker possesses, and are factors that contribute to work efficiency and results.

[0102] "Means of objective judgment" are methods or tools for collecting data on an individual's behavioral tendencies and thought patterns and evaluating them without subjectivity.

[0103] A "natural language processing tool" is software or algorithms that analyze text data and understand its meaning and intent.

[0104] "Judgment results" are the data or information obtained after an objective evaluation of an individual's strengths.

[0105] The "specific action suggestions" are specific actions or work contents that are recommended to the worker based on the judgment results.

[0106] A "means for allocating workers to optimal tasks" is a method or system for allocating workers to the most suitable tasks or roles, taking into account their strengths and characteristics.

[0107] The system for carrying out the present invention is for objectively determining the strengths of individuals and allocating workers to the most suitable tasks based on the results. A specific embodiment of this system will be described below.

[0108] System Configuration

[0109] The system consists of the following main components:

[0110] 1. A means to objectively assess an individual's strengths: This is software that collects and analyzes data on the behavioral tendencies and thought patterns of workers. Specifically, it uses sensors and log data to record and analyze the behavior of workers.

[0111] 2. Natural Language Processing Tools: These tools are used to analyze the collected data and identify individual strengths. They use Python’s NLTK library and scikit-learn to analyze text data.

[0112] 3. Means for outputting specific action suggestions: Based on the judgment results obtained by the natural language processing tool, specific action suggestions are generated for the worker. Using the generative AI model, a prompt sentence is input and the optimal action suggestion is generated.

[0113] 4. Means for allocating workers to optimal tasks: This is an algorithm for allocating workers to optimal tasks based on action suggestions. Using KMeans clustering, we classify workers into appropriate groups and allocate tasks optimally.

[0114] Program processing explanation

[0115] The server first collects data on the behavior of workers. This is done using sensor and log data. The collected data is then analyzed using natural language processing tools. Specifically, the NLTK library is used to tokenize the text data and perform TF-IDF vectorization. After that, the workers are classified into clusters using scikit-learn's KMeans clustering.

[0116] Next, a generative AI model is used to generate specific action suggestions based on the clustering results. A prompt is input, and the generative AI model outputs optimal action suggestions. Based on these action suggestions, workers are assigned to optimal tasks.

[0117] Examples

[0118] For example, let's say you have the following worker data:

[0119] Analyze the behavioral trends of workers and propose optimal work placement. Below is the worker data.

[0120] [

[0121] {"name": "A", "behavior": "Works quickly. Good problem-solving skills."},

[0122] {"name": "B", "behavior": "Good at detailed work. Works carefully."},

[0123] {"name": "C", "behavior": "Emphasis on teamwork. Excellent communication skills."}

[0124] ]

[0125] Based on this data, the system identifies the strengths of each worker and suggests optimal task allocations. For example, Worker A, who works quickly, can be assigned to tasks that require emergency response. Worker B, who excels at detailed work, can be assigned to precision work. Worker C, who values ​​teamwork, can be assigned as a team leader.

[0126] In this way, the system makes the most of workers' strengths and achieves efficient work allocation.

[0127] The flow of the specific process in the application example 1 will be described with reference to FIG.

[0128] Step 1:

[0129] The server collects the worker's behavior data. Specifically, it records the worker's behavior using sensors and log data. The inputs include the worker's behavior log and sensor data. These data are stored in a database for subsequent analysis. The output is the collected behavior data.

[0130] Step 2:

[0131] The server preprocesses the collected behavioral data. Specifically, it uses a natural language processing tool (NLTK library) to tokenize the text data, remove non-alphabetical characters, and remove stop words. The input is the behavioral data collected in step 1. The output is the preprocessed text data.

[0132] Step 3:

[0133] The server converts the preprocessed text data into a TF-IDF vector. Specifically, it uses scikit-learn's TfidfVectorizer to convert the text data into a numerical vector. The input is the text data preprocessed in step 2. The output is a TF-IDF vector.

[0134] Step 4:

[0135] The server performs clustering using the TF-IDF vectors. Specifically, it uses scikit-learn's KMeans clustering algorithm to classify workers into multiple clusters. The input is the TF-IDF vector obtained in step 3. The output is the cluster information for each worker.

[0136] Step 5:

[0137] The server generates specific action suggestions based on the clustering results. Specifically, the generative AI model is used to input a prompt sentence and generate optimal action suggestions. The input is the cluster information and the prompt sentence. The output is the generated action suggestions.

[0138] Step 6:

[0139] The server assigns workers to optimal tasks based on the generated action proposals. Specifically, it analyzes the action proposals and executes an algorithm to assign optimal tasks to each worker. The input is the action proposals generated in step 5. The output is optimal task assignment information.

[0140] Step 7:

[0141] The server notifies the workers of the optimal work allocation information. Specifically, it uses a notification system to notify each worker of the new work allocation. The input is the optimal work allocation information obtained in step 6. The output is the notification to the workers.

[0142] Example 2

[0143] Next, a second embodiment of the second embodiment will be described. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0144] Although conventional systems can objectively judge an individual's strengths, it is difficult to generate suggestions for linking those strengths to concrete actions. In addition, it is not clear how the generated action suggestions can be used for individual self-improvement and management, so the actual effect is limited.

[0145] The identification process by the identification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes a means for objectively judging the strengths of an individual, a means for loading the judgment result into a natural language processing tool, a means for the natural language processing tool to generate a specific action proposal based on the judgment result, and a means for outputting the action proposal. This makes it possible to automatically generate a specific action proposal for making the most of an individual's strengths, and to effectively utilize the action proposal for the individual's self-improvement and management.

[0146] "Individual strengths" refer to the specific abilities or characteristics that an individual possesses, in which they excel compared to others.

[0147] "Judgment objectively" means making an evaluation based on data and facts, without being influenced by subjectivity or emotion.

[0148] A "natural language processing tool" refers to software and algorithms for analyzing text data and understanding its meaning and structure.

[0149] "Judgment results" refer to the results of an objective evaluation of an individual's strengths.

[0150] "Action suggestions" refer to specific actions that individuals can take to make the most of their strengths.

[0151] "Outputting" refers to providing the generated information in a form usable by a user.

[0152] "Self-improvement" refers to the efforts and activities that an individual undertakes to improve his or her own abilities and knowledge.

[0153] "Management" refers to the operation and management of an organization or project.

[0154] The present invention is a system for objectively determining the strengths of an individual and generating specific action proposals based on the results of the determination. A specific embodiment of this system will be described below.

[0155] The server first collects data to objectively determine an individual's strengths. This data is obtained from various sources, such as survey results and performance evaluations. The server then analyzes this data to identify the individual's strengths.

[0156] The server then feeds the results of the identified strengths into a natural language processing tool. Specifically, the server uses spaCy, a Python natural language processing library, which is used to tokenize the text data and extract key keywords and phrases.

[0157] The server uses natural language processing tools to analyze the results of the judgment and generates specific action suggestions based on the results. For example, if the report states that "this individual has excellent team leadership," the server generates action suggestions such as "serve as a leader for team projects" and "regularly communicate with team members."

[0158] The generated action proposal is provided to the user by the server. Specifically, the action proposal is output in text format and can be viewed by the user. This allows the user to take specific actions to make the most of their strengths.

[0159] As a concrete example, here is a prompt that a user can enter into a generative AI model:

[0160] "Please suggest what action individuals should take based on this report."

[0161] Examples of specific prompts include the following:

[0162] The report states:

[0163] Strengths: Team Leadership

[0164] Details: This individual has excellent team building skills and excels at project management.

[0165] Action suggestion:

[0166] Lead a team project

[0167] Communicate with team members regularly

[0168] Regularly review project progress

[0169] In this way, the server analyzes the contents of the report and generates and outputs specific action proposals for individuals to make the most of their strengths, which can be effectively used for self-improvement and management of individuals.

[0170] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0171] Step 1: Load the report

[0172] The server reads the report output from the strengths assessment tool. Specifically, the server specifies the file path where the report is saved, opens the file, and obtains the contents. The file path of the report is required as input, and the contents of the report are obtained in text format as output.

[0173] Step 2: Analyze the report

[0174] The server analyzes the report content using natural language processing tools. Specifically, the server uses spaCy, a Python natural language processing library, to tokenize the report text and extract important keywords and phrases. The input is the report text, and the output is the extracted keywords and phrases.

[0175] Step 3: Generate action suggestions

[0176] The server generates specific action suggestions based on the analysis results. Specifically, the server suggests actions that individuals can take to make the most of their strengths based on the extracted keywords and phrases. For example, if the keyword "team leadership" is extracted, the server generates action suggestions such as "serve as a leader in a team project." The input requires the extracted keywords and phrases, and the output is a specific action suggestion.

[0177] Step 4: Output action suggestions

[0178] The server provides the generated action proposal to the user. Specifically, the server outputs the action proposal in a text format so that the user can view it. The generated action proposal is required as an input, and the action proposal in a format viewable by the user is obtained as an output.

[0179] In this way, the server analyzes the contents of the report and generates and outputs specific action proposals for individuals to make the most of their strengths, which can be effectively used for self-improvement and management of individuals.

[0180] (Application example 2)

[0181] Next, a description will be given of Application Example 2 of Form Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0182] Conventional factory robot systems have difficulty automatically generating specific action suggestions to maximize production efficiency. In addition, there was no system that could objectively determine an individual's strengths and output specific action suggestions based on them. As a result, it was not possible to effectively support the improvement of production efficiency or the self-improvement of individuals.

[0183] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0184] In this invention, the server includes a means for objectively judging the strengths of individuals, a means for loading the judgment result into a natural language processing tool, a means for the natural language processing tool to output a specific action proposal based on the judgment result, a means for analyzing a production report in the factory with the natural language processing tool, and a means for proposing what action each robot should take to maximize production efficiency. This makes it possible to effectively support the improvement of production efficiency and the self-improvement of individuals.

[0185] "Individual strengths" refer to the specific abilities or characteristics that an individual possesses, in which they excel compared to others.

[0186] "Judgment objectively" means making an evaluation based on facts and data, without being influenced by subjectivity or emotion.

[0187] "Natural language processing tools" refer to technology and software that allows computers to analyze and understand human language.

[0188] An "action proposal" is a proposal that outlines specific actions or steps to be taken to achieve a particular goal.

[0189] An "in-factory production report" refers to a document that records the status and results of production activities in a factory.

[0190] "Analyze" refers to examining data or information in detail to clarify its structure and meaning.

[0191] "Production efficiency" refers to the ratio of production results obtained to the resources input, and is an indicator of efficient production activities.

[0192] A "robot" refers to a mechanical device that performs work automatically, especially those used in production activities in factories and other places.

[0193] To "propose" means to present a solution or plan of action for a particular problem or challenge.

[0194] A system for carrying out the present invention has the following configuration: A server includes means for objectively judging the strengths of individuals, means for loading the judgment results into a natural language processing tool, means for the natural language processing tool to output specific action suggestions based on the judgment results, means for analyzing production reports within the factory with the natural language processing tool, and means for proposing what actions each robot should take to maximize production efficiency.

[0195] Program processing explanation

[0196] The server first collects data to objectively judge an individual's strengths. This data includes the individual's past performance, evaluations, skill sets, etc. Next, the collected data is loaded into a natural language processing tool to analyze the individual's strengths. For this analysis, a Japanese natural language processing model is loaded using the spacy library, and a summary is generated using the transformers library pipeline.

[0197] Based on the analysis, natural language processing tools suggest how individuals can take action to make the most of their strengths, using generative AI models to generate specific action suggestions.

[0198] In addition, the system uses natural language processing tools to analyze production reports from within the factory and proposes what actions each robot should take to maximize production efficiency. This analysis involves examining the contents of the reports in detail and processing and calculating data to clarify their structure and meaning.

[0199] Examples

[0200] As a concrete example, we use a report on production efficiency within a factory as input. Below is an example of a prompt sentence to be input to the generative AI model.

[0201] This is a report on production efficiency in a factory. In the current production line, a bottleneck occurs in a specific process. In order to eliminate this bottleneck, it is necessary to optimize the operation of the robots. Specifically, production efficiency can be improved by adjusting the timing of material supply and the operating speed of each robot.

[0202] Taking this prompt as input, the server generates the following action suggestions:

[0203] Adjust the timing of material supply.

[0204] Adjust the movement speed of each robot.

[0205] This makes it possible to provide specific action suggestions for factory robots to maximize production efficiency.

[0206] The flow of the specific process in the application example 2 will be described with reference to FIG.

[0207] Step 1:

[0208] The server collects data to objectively determine an individual's strengths.

[0209] Inputs: Data such as an individual’s past performance, ratings, and skill sets.

[0210] Output: The collected data.

[0211] Specific operation: The server retrieves data on individual performance and evaluations from databases and external systems and stores this in an internal database.

[0212] Step 2:

[0213] The server loads the collected data into a natural language processing tool to analyze each individual's strengths.

[0214] Input: Collected data.

[0215] Output: Analysis of individual strengths.

[0216] How it works: The server loads a Japanese natural language processing model using the spacy library and analyzes the collected data. The analysis results are output as text data showing the individual's strengths.

[0217] Step 3:

[0218] The server generates specific action suggestions based on the analysis results.

[0219] Input: Personal strengths analysis results.

[0220] Output: Specific suggestions for action.

[0221] Specific Actions: The server uses a generative AI model to generate action suggestions that show an individual what actions to take to best utilize their strengths.

[0222] Step 4:

[0223] The server analyzes production reports from within the factory using natural language processing tools.

[0224] Input: In-factory production report.

[0225] Output: Analysis results of production report.

[0226] Specific operation: The server uses the transformers library pipeline to generate a summary of the production report and perform detailed analysis of the report contents.

[0227] Step 5:

[0228] Based on the analysis results, the server suggests what actions each robot should take to maximize production efficiency.

[0229] Input: Analysis results of production report.

[0230] Output: Specific suggestions for action.

[0231] Specific actions: The server uses the generative AI model to generate specific action suggestions to improve production efficiency, for example, making suggestions on adjusting the timing of material supply or the speed of robot movements.

[0232] Step 6:

[0233] The server provides the generated action suggestions to the user.

[0234] Input: Specific proposals for action.

[0235] Output: Action suggestions provided to the user.

[0236] Specific operation: The server sends the generated action proposal to the user's terminal so that the user can review it.

[0237] Example 3

[0238] Next, a third embodiment of the third embodiment will be described. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0239] In conventional personnel allocation systems, it was difficult to fully utilize the strengths of individuals, and personnel were often not assigned to appropriate tasks. In addition, there was a lack of means to objectively judge individuals' strengths and generate specific action proposals based on them, making it difficult for management to make effective personnel allocations.

[0240] The identification process by the identification processing unit 290 of the data processing device 12 in the third embodiment is realized by the following means. In this invention, the server includes a means for objectively judging the strengths of individuals, a means for loading the judgment result into a natural language processing tool, a means for the natural language processing tool to input a prompt sentence into a generative AI model based on the judgment result and output a specific action proposal, and a means for providing the action proposal to management. This enables personnel allocation that makes the most of individual strengths.

[0241] "Individual strengths" are specific abilities or characteristics that an individual possesses, and are the factors that enable them to perform better than others in a task or activity.

[0242] "Means of objective judgment" are methods or tools for accurately evaluating an individual's strengths based on data and evaluation criteria, without relying on subjectivity.

[0243] A "natural language processing tool" is software or algorithms for analyzing text data and understanding its meaning.

[0244] A "generative AI model" is an artificial intelligence model that generates new information or suggestions based on input data.

[0245] A "prompt" is an instruction or question input to a generative AI model that triggers the model to generate an appropriate output.

[0246] "Action suggestions" are suggestions that provide specific actions or work instructions based on an individual's strengths and analysis results.

[0247] "Management" refers to the people or departments responsible for running and managing an organization or team.

[0248] The present invention is a system for objectively determining the strengths of an individual and generating specific action proposals based on the results. A specific embodiment of this system is described below.

[0249] Hardware and Software Used

[0250] Hardware: Servers, terminals (PCs and smartphones)

[0251] Software: Generative AI models (e.g., GPT-4 (registered trademark)), natural language processing tools (e.g., SpaCy)

[0252] System Overview

[0253] The system starts with the user accessing the strengths assessment tool using a terminal and inputting information on self-evaluation and work performance. The server receives the data sent by the user and analyzes it using natural language processing tools. Based on the analysis results, it inputs prompt sentences into the generative AI model to generate specific action suggestions. Finally, the server provides the generated action suggestions to management.

[0254] Examples

[0255] 1. The user accesses the strengths assessment tool and enters information

[0256] The user uses the terminal to access the web page or application of the strengths assessment tool, answers questions about self-evaluation and work performance, and inputs the required information.

[0257] Example: A user answers "Strategic planning" to the question "What do you do best?"

[0258] 2. The server receives and analyzes the user input data

[0259] The server receives the data sent by the user and analyzes it using a natural language processing tool (e.g. SpaCy). As a result of the analysis, the user's strengths are identified.

[0260] Example: The server parses the answer "strategic planning" and identifies the user's strength as "strategic thinking."

[0261] 3. The server inputs a prompt sentence into the generative AI model based on the analysis results and generates action suggestions.

[0262] Based on the analysis results, the server inputs a prompt sentence into a generative AI model (e.g., GPT-4), which then generates a specific action suggestion based on the prompt sentence.

[0263] Example: The server inputs the prompt sentence "This individual's strength is strategic thinking. Please suggest what kind of work this individual should be involved in to utilize this strength" to the generative AI model, and the generative AI model generates an action suggestion such as "Suggest involving this individual in strategic planning and business planning."

[0264] 4. The server provides the generated action proposals to the management.

[0265] The server provides the generated action proposals to management, who then receives the proposals and assigns personnel to maximize the use of each individual's strengths.

[0266] Example: The server sends an action proposal to management, such as "I suggest that this individual be involved in strategic planning and business planning," and management assigns the relevant individual to the appropriate task based on that proposal.

[0267] In this way, the system supports personnel allocation that makes the most of each individual's strengths. The flow of the identification process in the third embodiment will be described with reference to FIG.

[0268] Step 1:

[0269] The user accesses the strengths assessment tool and inputs information.

[0270] Specific actions: The user uses the terminal to access the strengths assessment tool web page or application. The user answers questions about self-evaluation and work performance and enters the required information.

[0271] Input: Information about the user's self-assessment and job performance.

[0272] Output: The user's input data.

[0273] Step 2:

[0274] The server receives and analyzes the user's input data.

[0275] Specific operation: The server receives the data sent by the user and analyzes the data using a natural language processing tool (e.g. SpaCy). As a result of the analysis, the user's strengths are identified.

[0276] Input: Data entered by the user.

[0277] Output: Analysis results identifying user strengths.

[0278] Step 3:

[0279] Based on the analysis results, the server inputs prompt sentences into the generative AI model and generates action suggestions.

[0280] Specific action: Based on the analysis results, the server inputs a prompt sentence into the generative AI model (e.g. GPT-4). The generative AI model generates specific action suggestions based on the prompt sentence.

[0281] Input: Analysis result and prompt.

[0282] Output: Specific action suggestions from the generative AI model.

[0283] Step 4:

[0284] The server provides the generated action suggestions to the management.

[0285] Specific operation: The server provides the generated action proposals to management. Management receives the proposals and assigns personnel to make the most of each individual's strengths.

[0286] Input: Generated action suggestions.

[0287] Output: Action suggestions provided to management.

[0288] (Application example 3)

[0289] Next, a description will be given of Application Example 3 of Form Example 3. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0290] In conventional personnel allocation systems, the strengths of each worker could not be fully utilized, and optimal work allocation was often not performed. As a result, there were problems with reduced work efficiency and lack of improvement in productivity. In addition, there was a lack of means to objectively judge the strengths of workers and propose specific actions based on that, making it difficult for management to perform appropriate personnel allocation.

[0291] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 3 is realized by the following means.

[0292] In this invention, the server includes a means for objectively judging the strengths of individuals, a means for inputting the judgment result into a natural language processing tool, a means for the natural language processing tool to output a specific action proposal based on the judgment result, and a means for proposing an optimal task allocation for workers based on the action proposal, thereby enabling optimal task allocation that makes the most of the strengths of each worker.

[0293] "Individual strengths" refers to the unique abilities, skills, and areas of expertise that a particular individual possesses.

[0294] "Means of objective judgment" refers to a method of accurately evaluating an individual's strengths based on data and evaluation criteria, without relying on subjectivity.

[0295] "Natural language processing tools" refers to computer programs and algorithms that understand, analyze, and generate human language.

[0296] "Judgment results" refers to data and information obtained as a result of an objective evaluation of an individual's strengths.

[0297] "Specific action suggestions" refer to suggestions that specifically indicate what actions an individual should take based on the judgment results.

[0298] "Optimal worker allocation" refers to the allocation of workers to perform tasks most efficiently and effectively based on their strengths and capabilities.

[0299] A "server" refers to a computer system that processes and stores data on a network.

[0300] The system for carrying out the present invention objectively judges the strengths of individuals and proposes optimal work allocation based on the results. A specific embodiment of this system will be described below.

[0301] The server first collects data to objectively determine an individual's strengths. This data can come from the worker's past performance, skill assessments, feedback, etc. The server then loads this data into a natural language processing tool. This natural language processing tool uses OpenAI® APIs and includes a generative AI model to analyze individual strengths.

[0302] The natural language processing tool analyzes the collected data and identifies the strengths of the individual. For example, if a worker is good at precision work, "precision work" is identified as the worker's strength. The result of this judgment is sent to the server.

[0303] Next, the server generates specific action suggestions based on the results of this judgment. For example, a suggestion is generated to assign a worker who is good at precision work to the assembly of precision equipment. This action suggestion is used to determine the optimal task allocation of workers.

[0304] As a concrete example, by inputting the following prompt sentences into a generative AI model, we can obtain optimal work placement suggestions:

[0305] Worker strengths data:

[0306] Person A: Precision work

[0307] Person B: Physical strength

[0308] Person C: Strategic thinking

[0309] Work content and required strengths:

[0310] Precision equipment assembly: precision work

[0311] Lifting heavy objects: Physical strength

[0312] Production Line Optimization: Strategic Thinking

[0313] Based on the above data, please suggest the optimal work arrangement.

[0314] By inputting this prompt into a generative AI model, the server can obtain optimal work placement suggestions, resulting in efficient work placement that makes the most of the strengths of each worker.

[0315] The hardware used is a computer system that processes and stores data over a network, and the software uses Python and OpenAI APIs, which makes it possible to analyze the strengths of each worker and propose optimal work placement.

[0316] The flow of the specific process in the application example 3 will be described with reference to FIG.

[0317] Step 1:

[0318] The server collects data to objectively judge the strengths of workers. As input, it receives data such as the worker's past performance, skill evaluation, and feedback, and stores it in a database. As output, it obtains the collected data.

[0319] Step 2:

[0320] The server loads the collected data into a natural language processing tool. As input, it uses the data collected in step 1 and sends the data to the natural language processing tool. As output, it gets the data in a format that the natural language processing tool can parse.

[0321] Step 3:

[0322] The natural language processing tool analyzes the input data and identifies the strengths of the workers. As input, it uses the data obtained in step 2 and performs analysis using a generative AI model. As output, data is obtained in which the strengths of each worker are identified.

[0323] Step 4:

[0324] The server generates specific action suggestions based on the strengths data obtained from the natural language processing tool. As input, it uses the strengths data obtained in step 3 and inputs prompt sentences into the generative AI model. As output, it obtains specific action suggestions for each worker.

[0325] Step 5:

[0326] The server proposes an optimal task placement for workers based on the generated action proposals. As input, it uses the action proposals obtained in step 4 and matches the tasks with the required strengths. As output, it obtains an optimal task placement proposal.

[0327] Step 6:

[0328] The server notifies the workers and management of the optimal work placement proposal. As input, it uses the work placement proposal obtained in step 5 and sends information to the workers and management via the notification system. As output, the workers and management receive the optimal work placement proposal.

[0329] Furthermore, an emotion engine that estimates the emotion of the user may be combined. That is, the identification processing unit 290 may estimate the emotion of the user using the emotion identification model 59, and perform identification processing using the emotion of the user.

[0330] "Example 1"

[0331] In one embodiment of the present invention, a strengths assessment tool such as Gallup's StrengthsFinder is used as a means for objectively assessing an individual's strengths. This tool analyzes an individual's behavioral tendencies and thought patterns, and outputs the results as a report. Next, a natural language processing tool reads this report. This tool analyzes the contents of the report and generates specific action suggestions based on the results. Furthermore, an emotion engine recognizes the user's emotions and generates specific action suggestions based on the emotions. Specifically, if the user is feeling joy, an action that will increase the joy is suggested. Also, if the user is feeling sad, an action that will reduce the sadness is suggested.

[0332] "Example 2"

[0333] In another embodiment of the present invention, the emotion engine generates specific action suggestions based on the user's emotions to support personal self-improvement, such as when the user is excited, action suggestions are made to leverage the excitement to learn new skills, and when the user is depressed, action suggestions are made to overcome depression.

[0334] "Example 3"

[0335] In yet another embodiment of the present invention, the emotion engine generates specific action suggestions to utilize the user's emotions for emotion management, for example, if the user is feeling happy, it suggests an action to share the happiness, and if the user is feeling angry, it suggests a dialogue or discussion to resolve the anger.

[0336] The process flow of each embodiment will be described below.

[0337] "Example 1"

[0338] Step 1: Users assess their own strengths using a strengths-determining tool such as Gallup's StrengthsFinder.

[0339] Step 2: The strengths assessment tool analyzes the user's behavioral tendencies and thought patterns and outputs the results in a report.

[0340] Step 3: A natural language processing tool reads the report and analyzes its content.

[0341] Step 4: Natural language processing tools generate specific action suggestions based on the analysis results.

[0342] Step 5: The emotion engine recognizes the user's emotion.

[0343] Step 6: The emotion engine generates specific action suggestions based on the emotions it recognizes.

[0344] "Example 2"

[0345] Step 1: The emotion engine recognizes the user's emotion.

[0346] Step 2: Based on the emotions recognized by the emotion engine, specific action suggestions are generated to support the individual's self-improvement.

[0347] "Example 3"

[0348] Step 1: The emotion engine recognizes the user's emotion.

[0349] Step 2: Based on the emotions recognized by the emotion engine, specific action suggestions are generated for use in management.

[0350] Example 1

[0351] Next, a description will be given of Example 1 of the embodiment 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal".

[0352] Conventional systems for assessing individual strengths lacked specific action suggestions that utilize the results of the strength assessment, which meant that users could not effectively utilize the results in self-improvement and management. In addition, the system did not take into account the user's emotions when proposing actions, which meant that appropriate support was not provided according to the user's emotional state.

[0353] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0354] In this invention, the server includes a means for objectively judging an individual's strengths, a means for loading the judgment result into a natural language processing tool, a means for the natural language processing tool to output a specific action proposal based on the judgment result, a means for recognizing the user's emotion using an emotion recognition engine, and a means for generating an action proposal according to the emotion based on the result of the emotion recognition engine. This makes it possible to propose a specific action that makes use of the user's strengths, and further to provide appropriate support according to the user's emotional state.

[0355] "Means for objectively assessing individual strengths" refers to tools or algorithms that analyze an individual's behavioral tendencies and thought patterns and identify their strengths based on the results.

[0356] A "natural language processing tool" is software or algorithms used to analyze text data and understand and process its content.

[0357] An "emotion recognition engine" is software or algorithms used to analyze a user's emotional state and identify those emotions.

[0358] The "means for outputting action suggestions" refers to a function or algorithm for suggesting specific actions to the user based on the analysis results.

[0359] A "means for generating action suggestions according to emotions" is a function or algorithm for taking into account the emotional state of the user and suggesting actions appropriate to those emotions.

[0360] This invention is a system that objectively judges the strengths of individuals and proposes specific actions based on the results. This system works in cooperation with a server, a terminal, and a user.

[0361] First, the user uses a terminal to input information about his / her own behavioral tendencies and thought patterns. This information is collected through questionnaires or self-evaluation sheets. The terminal then transmits the user's response data to a server.

[0362] The server uses the received user data to objectively determine the strengths of the individual. Specifically, it uses a strengths assessment tool such as Gallup's StrengthsFinder tool. The server inputs the user data into this tool and analyzes the individual's behavioral tendencies and thought patterns. The analysis results are generated as a report and saved in text format.

[0363] Next, the server passes the generated report to a natural language processing tool (e.g., Google® Cloud Natural Language API) to analyze the contents. The natural language processing tool analyzes the text data of the report and returns the results to the server. Based on the analysis results, the server generates specific action suggestions that utilize the user's strengths. For example, if the user's strength is "leadership," the server makes specific action suggestions to demonstrate leadership.

[0364] Furthermore, the server recognizes the user's emotions using an emotion recognition engine (e.g., IBM Watson (registered trademark) Tone Analyzer). The user's emotion data is obtained from input from the terminal and past behavioral history. The emotion recognition engine analyzes the user's emotional state and returns the result to the server. Based on the emotion analysis result, the server generates specific action suggestions according to the user's emotions. For example, if the user is feeling happy, the server suggests actions that will increase that happiness. Also, if the user is feeling sad, the server suggests actions that will reduce that sadness.

[0365] As a concrete example, let us consider a case where the user is determined to have strengths in "leadership" and "empathy." The server generates the following action suggestions:

[0366] Demonstrate leadership by taking the lead in setting goals for your team.

[0367] Use your empathy and actively listen to your team members' opinions.

[0368] If the emotion engine recognizes the user's emotions and determines that the user is feeling happy, it will suggest the following actions:

[0369] Share success stories with your team to amplify the joy.

[0370] If the user is feeling sad, the following action suggestions are made:

[0371] To ease your grief, set aside time to talk with a trusted colleague.

[0372] Example prompt:

[0373] Analyze user strengths and generate specific action suggestions based on user behavioral tendencies and thought patterns. Consider user emotions and suggest actions to increase joy or reduce sadness.

[0374] In this way, a system is realized in which the server, terminal, and user work together to objectively judge an individual's strengths and provide specific suggestions for action.

[0375] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0376] Step 1:

[0377] The user uses the terminal to input information about his / her own behavioral tendencies and thought patterns. The input information is collected through questionnaires or self-evaluation sheets. The terminal transmits the user's response data to the server.

[0378] Input: Information about the user's behavioral tendencies and thought patterns

[0379] Output: User data sent to the server.

[0380] Specific operation: The user answers questions displayed on the device screen, and the device sends the data to the server.

[0381] Step 2:

[0382] The server uses the received user data to objectively judge the strengths of the individual. Specifically, it uses a strengths judgment tool. The server inputs the user data into this tool and analyzes the individual's behavioral tendencies and thought patterns.

[0383] Input: User data

[0384] Output: Analysis results from the strengths assessment tool

[0385] Specific operation: The server calls the API of the strengths assessment tool, sends user data, and receives the analysis results.

[0386] Step 3:

[0387] The server generates a report summarizing the user's strengths based on the analysis results obtained from the strengths assessment tool, and saves the report in text format.

[0388] Input: Analysis results of strengths assessment tool

[0389] Output: Text report

[0390] Specific operation: The server converts the analysis results into a text report and stores it in a database.

[0391] Step 4:

[0392] The server passes the generated report to a natural language processing tool for content analysis. The natural language processing tool analyzes the text data of the report and returns the results to the server.

[0393] Input: Text report

[0394] Output: Analysis results from natural language processing tools

[0395] Specific operation: The server sends the report's text data to a natural language processing tool and receives the analysis results.

[0396] Step 5:

[0397] The server generates specific action suggestions that utilize the user's strengths based on the analysis results obtained from the natural language processing tool.

[0398] Input: Analysis results of natural language processing tools

[0399] Output: Specific action suggestions

[0400] Specific operation: The server runs an algorithm to generate action suggestions based on the analysis results, and generates the action suggestions in text format.

[0401] Step 6:

[0402] The server uses an emotion recognition engine to recognize the user's emotions. The user's emotion data is obtained from input from the terminal and from the user's past behavior history.

[0403] Input: User emotion data

[0404] Output: Emotion analysis results by the emotion recognition engine

[0405] Specific operation: The user inputs his / her current emotion through the terminal, and the server sends the emotion data to the emotion recognition engine and receives the analysis results.

[0406] Step 7:

[0407] The server generates specific action suggestions according to the user's emotions based on the emotion analysis results obtained from the emotion recognition engine.

[0408] Input: Emotion analysis results from the emotion recognition engine

[0409] Output: Specific action suggestions based on emotions

[0410] Specific operation: The server runs an algorithm that generates action suggestions based on the results of emotion analysis. If the user is feeling happy, the server suggests actions that will increase that joy, and if the user is feeling sad, the server suggests actions that will reduce that sadness.

[0411] (Application example 1)

[0412] Next, a description will be given of Application Example 1 of Form Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0413] Conventional tools for determining individual strengths identify strengths by analyzing an individual's behavioral tendencies and thought patterns, but it is difficult to link the results to specific action suggestions. In addition, since action suggestions do not take into account the user's emotional state, there is a problem in that appropriate suggestions cannot be made according to the user's current emotions. Furthermore, there is a lack of concrete measures to personalize shopping experiences in physical stores.

[0414] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0415] In this invention, the server includes a means for objectively judging an individual's strengths, a means for loading the judgment result into a natural language processing tool, a means for the natural language processing tool to output a specific action proposal based on the judgment result, a means for recognizing a user's emotion, a means for generating an action proposal based on the emotion, and a means for proposing optimal products and services based on the user's strengths and emotional state. This makes it possible to propose specific actions according to the user's strengths and emotional state, thereby personalizing the shopping experience at a brick-and-mortar store.

[0416] "Means of objectively assessing an individual's strengths" refers to a method for analyzing an individual's behavioral tendencies and thought patterns and identifying that individual's strengths based on the results.

[0417] The "means for reading the judgment result into a natural language processing tool" refers to a means for inputting the result of judging an individual's strengths into a natural language processing tool.

[0418] "The means by which the natural language processing tool outputs specific action suggestions based on the judgment results" refers to the means by which the natural language processing tool analyzes the judgment results of an individual's strengths and generates specific action suggestions based thereon.

[0419] A "means for recognizing a user's emotion" is a means for detecting and recognizing a user's current emotional state.

[0420] The "means for generating action suggestions based on the emotion" refers to means for generating appropriate action suggestions based on the recognized emotional state of the user.

[0421] The "means for proposing optimal products and services based on the user's strengths and emotional state" refers to a means for proposing optimal products and services taking into account the user's strengths and current emotional state.

[0422] A system for implementing this invention includes means for objectively judging an individual's strengths, means for loading the judgment result into a natural language processing tool, means for the natural language processing tool to output specific action suggestions based on the judgment result, means for recognizing the user's emotions, means for generating action suggestions based on the emotions, and means for suggesting optimal products and services based on the user's strengths and emotional state.

[0423] Program processing explanation

[0424] Hardware and software used

[0425] Hardware: Smartphone

[0426] Software: Python, TextBlob, Transformers (Hugging Face)

[0427] Data processing and calculation

[0428] 1. A means of objectively assessing an individual's strengths: The server uses tools to analyze an individual's behavioral tendencies and thought patterns, and outputs the results as a report in JSON format.

[0429] 2. Means for inputting the judgment result into a natural language processing tool: The server inputs the generated report into a natural language processing tool (TextBlob) and performs text analysis.

[0430] 3. Means for the natural language processing tool to output specific action suggestions based on the judgment result: The natural language processing tool generates action suggestions based on the analysis result.

[0431] 4. Means for recognizing user's emotions: The server uses Hugging Face's Transformers to recognize the user's emotional state.

[0432] 5. Means for generating action suggestions based on the emotion: The server generates appropriate action suggestions based on the recognized emotional state.

[0433] 6. Means for suggesting optimal products and services based on the user's strengths and emotional state: The server suggests optimal products and services taking into account the user's strengths and emotional state.

[0434] Examples

[0435] When a user enters a physical store, the application installed on the smartphone automatically starts. The application analyzes the user's strengths and current emotional state, and if the user has a "positive emotion," for example, the application makes a suggestion such as "Try these products by utilizing your strengths."

[0436] Examples of prompt statements

[0437] Recommend the best products and services based on the user's strengths and emotional state. If the user is feeling positive, suggest products that play to their strengths, if they are feeling negative, suggest products to lift their mood.

[0438] The flow of the specific process in the application example 1 will be described with reference to FIG.

[0439] Step 1:

[0440] The server uses tools to analyze an individual's behavioral tendencies and thought patterns, and outputs the results as a report in JSON format. The input is an individual's behavioral data and thought pattern data, and the output is a report that identifies the individual's strengths. Specifically, the server collects behavioral data and applies an analysis algorithm to identify strengths.

[0441] Step 2:

[0442] The server inputs the generated report into a natural language processing tool (TextBlob) and performs text analysis. The input is the report generated in step 1, and the output is the analysis results. Specifically, the report text is read and sentiment analysis and keyword extraction are performed using TextBlob.

[0443] Step 3:

[0444] The natural language processing tool generates action suggestions based on the analysis results. The input is the analysis results obtained in step 2, and the output is specific action suggestions. Specifically, the tool applies an action suggestion algorithm based on the analysis results to generate action suggestions suitable for the user.

[0445] Step 4:

[0446] The server uses Hugging Face Transformers to recognize the user's emotional state. The input is text data that indicates the user's current emotion, and the output is the emotion recognition result. Specifically, the server inputs the user's text data into the Transformers and obtains emotion labels.

[0447] Step 5:

[0448] The server generates appropriate action suggestions based on the recognized emotional state. The input is the emotion recognition result obtained in step 4, and the output is the emotion-based action suggestions. Specifically, the server applies an action suggestion algorithm based on the emotion recognition result to generate action suggestions according to the user's emotions.

[0449] Step 6:

[0450] The server proposes optimal products and services taking into account the user's strengths and emotional state. The input is the action proposal obtained in step 3 and the action proposal based on the emotion obtained in step 5, and the output is the optimal product or service proposal. Specifically, the server integrates both proposals and selects and proposes the optimal product or service to the user.

[0451] Example 2

[0452] Next, a second embodiment of the second embodiment will be described. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0453] Conventional systems can objectively judge an individual's strengths, but it is difficult to provide specific action suggestions to make the most of those strengths. It is also difficult to generate action suggestions based on the user's emotional state. This has led to the problem that effective support cannot be provided for individual self-improvement and management.

[0454] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0455] In this invention, the server includes a means for objectively judging the strengths of an individual, a means for loading the judgment result into a natural language processing tool, a means for the natural language processing tool to output a specific action proposal based on the judgment result, a means for collecting emotion data of a user, a means for analyzing the emotion data with an emotion analysis tool, and a means for the emotion analysis tool to output a specific action proposal based on the emotion data. This makes it possible to provide a specific action proposal based on an individual's strengths and emotional state.

[0456] An "objective means of assessing individual strengths" is a method or device for evaluating an individual's characteristics and capabilities and identifying their strengths based on objective criteria.

[0457] "Natural language processing tools" are software and algorithms that analyze text data and understand meaning and sentiment.

[0458] The "means for loading the judgment results into a natural language processing tool" refers to a method or device for inputting the results of judging an individual's strengths into a natural language processing tool.

[0459] The "means for outputting specific action suggestions" refers to a method or device for suggesting specific actions that an individual should take based on the analysis results.

[0460] A "means for collecting user emotional data" is a method or device for measuring a user's emotional state and collecting that data.

[0461] An "emotion analysis tool" is software or algorithms that analyze collected emotion data and identify a user's emotional state.

[0462] The "means for outputting specific action suggestions based on emotion data" refers to a method or device for suggesting specific actions that a user should take based on the results of an emotion analysis tool.

[0463] The present invention is a system for generating specific action suggestions based on an individual's strengths and emotional state. A specific embodiment of the system will be described below.

[0464] First, we generate a program for the system that combines natural language processing and sentiment analysis tools to generate specific action suggestions based on the user's strengths and emotions.

[0465] Hardware and Software Used

[0466] Server: Receives data, analyzes it, and generates action suggestions.

[0467] Terminal: Collects user emotion data.

[0468] Natural language processing tools: Text analysis tools such as Google Cloud Natural Language API.

[0469] Sentiment analysis tools: Sentiment analysis tools such as IBM Watson Tone Analyzer.

[0470] Generative AI models: Generative AI models such as OpenAI GPT-3(registered trademark).

[0471] Data processing and calculation

[0472] 1. Receive a report from the strengths assessment tool

[0473] The server receives the report output from the strengths assessment tool. The report is provided in JSON format, PDF format, etc.

[0474] 2. Analyze the report contents using natural language processing tools

[0475] The server uses the Google Cloud Natural Language API to analyze the report content. Specifically, the server sends the report's text data to the API and performs keyword extraction and sentiment analysis.

[0476] 3. Generate action suggestions based on the analysis results

[0477] Based on the analysis results, the server generates specific action suggestions using a generative AI model (e.g., OpenAI GPT-3). A prompt such as "Please generate specific action suggestions when leadership is a strength" is entered.

[0478] 4. Collect user sentiment data

[0479] The device collects the user's emotion data, which is obtained from the user's input or a wearable device (e.g., Fitbit or Apple Watch).

[0480] 5. Analyze the sentiment data with a sentiment analysis tool

[0481] The server uses IBM Watson Tone Analyzer to analyze the user's emotional data. Specifically, it sends the emotional data to an API to identify the user's emotional state (excited, depressed, etc.).

[0482] 6. Generate action suggestions based on emotions

[0483] The server uses a generative AI model to generate specific action suggestions based on the results of the emotion analysis tool. A prompt such as "If the user is excited, please generate action suggestions for learning a new skill" is entered.

[0484] Examples

[0485] 1. Examples of natural language processing tools

[0486] A user uses the strengths determination tool to generate a report.

[0487] The server receives the report and parses it using the Google Cloud Natural Language API.

[0488] The natural language processing tool analyzes the situation and finds that "leadership is a strength."

[0489] Natural language processing tools generate action suggestions such as "Lead the project."

[0490] 2. Specific examples of sentiment analysis tools

[0491] A user collects emotion data using a wearable device.

[0492] The server receives the emotion data and analyzes it using IBM Watson Tone Analyzer.

[0493] The sentiment analysis tool finds that the user is excited.

[0494] Sentiment analysis tools generate action suggestions such as "take an online course to learn a new skill."

[0495] Examples of prompt statements

[0496] "Analyze the Strengths Tool report and generate specific action suggestions where leadership is a strength."

[0497] "Generate action suggestions to learn a new skill if the user is excited about it."

[0498] In this way, the system generates specific action suggestions based on the user's strengths and emotions.

[0499] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0500] Step 1:

[0501] A server receives the report from the strengths determination tool.

[0502] Input: Report output from the strengths assessment tool (JSON, PDF, etc.).

[0503] How it works: The server downloads the report using an HTTP request.

[0504] Output: The downloaded report data.

[0505] Step 2:

[0506] The server analyzes the report contents using natural language processing tools.

[0507] Input: The downloaded report data.

[0508] How it works: The server uses the Google Cloud Natural Language API to send the report's text data to the API, which performs keyword extraction and sentiment analysis.

[0509] Output: Analysis results (keywords and sentiment information).

[0510] Step 3:

[0511] The server generates action suggestions based on the analysis results.

[0512] Input: Analysis results from natural language processing tools.

[0513] How it works: The server uses a generative AI model (e.g., OpenAI GPT-3) to generate specific action suggestions. Enter a prompt such as "Generate specific action suggestions if leadership is a strength."

[0514] Output: Generated action suggestions.

[0515] Step 4:

[0516] The terminal collects the user's emotion data.

[0517] Input: User emotion data (heart rate, activity level, etc.).

[0518] How it works: The device collects emotion data from a wearable device (e.g., Fitbit or Apple Watch).

[0519] Output: The collected emotion data.

[0520] Step 5:

[0521] The server analyzes the emotion data using an emotion analysis tool.

[0522] Input: Collected emotion data.

[0523] How it works: The server uses IBM Watson Tone Analyzer to send emotion data to the API to identify the user's emotional state (excited, depressed, etc.).

[0524] Output: Emotion analysis results.

[0525] Step 6:

[0526] The server generates action suggestions based on the emotions.

[0527] Input: Sentiment analysis results from the sentiment analysis tool.

[0528] How it works: The server uses the generative AI model to generate specific action suggestions, inputting a prompt such as "If the user is excited, generate action suggestions for learning a new skill."

[0529] Output: Generated action suggestions.

[0530] In this way, the system generates specific action suggestions based on the user's strengths and emotions.

[0531] (Application example 2)

[0532] Next, a description will be given of Application Example 2 of Form Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0533] Conventional systems can objectively judge an individual's strengths and suggest specific actions based on them, but they cannot suggest actions that take into account the individual's emotional state. Therefore, there is a need to provide appropriate action suggestions according to the individual's emotional state.

[0534] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0535] In this invention, the server includes a means for objectively judging the strengths of an individual, a means for loading the judgment result into a natural language processing tool, a means for the natural language processing tool to output a specific action proposal based on the judgment result, a means for analyzing the emotional state of the individual using an emotion analysis engine, and a means for generating a specific action proposal based on the emotional state. This makes it possible to make the most of the strengths of an individual and to propose an appropriate action according to the emotional state.

[0536] A "means for objectively assessing an individual's strengths" is a method or device for objectively evaluating an individual's abilities and characteristics and obtaining the results as data.

[0537] A "natural language processing tool" is software or algorithms used to analyze text data and understand and process its content.

[0538] The "means for outputting specific action suggestions" refers to a method or device for suggesting specific actions that an individual should take based on the analyzed data.

[0539] An "emotion analysis engine" is software or algorithms that analyze an individual's emotional state and obtain the results as data.

[0540] A "means for analyzing an individual's emotional state" is a method or device for analyzing an individual's emotions in real time and acquiring that state as data.

[0541] A "means for generating specific action suggestions based on emotional state" is a method or apparatus for suggesting specific actions for an individual to take based on the analyzed emotional data.

[0542] The system for carrying out the present invention objectively judges the strengths of an individual, proposes specific actions based on the results, and analyzes the emotional state of the individual to propose actions based on the emotions. A specific embodiment of this system will be described below.

[0543] Hardware and Software Used

[0544] Hardware: Smartphones, smart glasses

[0545] Software: Natural language processing tools (e.g. SpaCy), sentiment analysis engines (e.g. IBM Watson Tone Analyzer), generative AI models (e.g. OpenAI GPT-4)

[0546] Data processing and calculation

[0547] 1. A means to objectively assess individual strengths

[0548] The server acquires data for objectively judging the strengths of individuals. This data is collected, for example, from survey results and past performance data. Based on this data, the server uses a natural language processing tool (SpaCy) to analyze the strengths of individuals and generate evaluation results.

[0549] 2. Action suggestions using natural language processing tools

[0550] The server loads the acquired evaluation results into a natural language processing tool. The natural language processing tool analyzes the evaluation results and inputs a prompt sentence into a generative AI model (GPT-4) to generate specific action suggestions. For example, the following prompt sentence is used:

[0551] "Please suggest an approach that staff who are good at customer service should take when dealing with customers."

[0552] 3. Emotion analysis engine for analyzing emotional states

[0553] The server acquires the individual's emotional state in real time through a smartphone or smart glasses, and uses an emotion analysis engine (IBM Watson Tone Analyzer) to analyze the acquired emotional data and evaluate the individual's emotional state.

[0554] 4. Suggested actions based on emotional state

[0555] Based on the analyzed emotion data, the server inputs a prompt sentence into the generative AI model (GPT-4) to generate action suggestions according to the emotional state. For example, the following prompt sentence is used:

[0556] "Suggest actions to help staff feel refreshed if they are tired."

[0557] Examples

[0558] Proposal for utilizing strengths:

[0559] Staff A is good at serving customers. The server uses a natural language processing tool to suggest that "when a customer enters the store, greet them with a smile and listen carefully to their needs."

[0560] Emotion-based action suggestions:

[0561] If staff member B is tired, the server will use the sentiment analysis engine to suggest "take a 5-minute break and take a deep breath to refresh yourself."

[0562] In this way, a system can be realized that makes the most of an individual's strengths while suggesting appropriate actions based on the individual's emotional state.

[0563] The flow of the identification process in the application example 2 will be described with reference to FIG.

[0564] Step 1:

[0565] The server acquires data to objectively judge the strengths of individuals. Inputs include survey results and past performance data. Based on this data, a natural language processing tool (SpaCy) is used to analyze the strengths of individuals and generate evaluation results. The output is an evaluation result showing the strengths of each individual.

[0566] Step 2:

[0567] The server loads the acquired evaluation results into a natural language processing tool. The input includes the evaluation results generated in step 1. The natural language processing tool analyzes the evaluation results and inputs prompt sentences into a generative AI model (GPT-4) to generate specific action suggestions. The output is specific action suggestions based on the individual's strengths.

[0568] Step 3:

[0569] The server acquires the emotional state of an individual in real time through a smartphone or smart glasses. The input includes the user's emotional data. Using an emotion analysis engine (IBM Watson Tone Analyzer), the acquired emotional data is analyzed and the individual's emotional state is evaluated. The output is an evaluation result indicating the individual's emotional state.

[0570] Step 4:

[0571] Based on the analyzed emotion data, the server inputs a prompt sentence into the generative AI model (GPT-4) to generate action suggestions according to the emotional state. The input includes the evaluation result of the emotional state generated in step 3. The generative AI model generates specific action suggestions based on the emotional state. The output is a specific action suggestion according to the emotional state.

[0572] Step 5:

[0573] The terminal presents the specific action suggestions received from the server to the user. The input includes the action suggestions generated in steps 2 and 4. The terminal presents these action suggestions to the user visually or audibly. The output is the specific action suggestions received by the user.

[0574] In this way, a system can be realized that makes the most of an individual's strengths while suggesting appropriate actions based on the individual's emotional state.

[0575] Example 3

[0576] Next, a third embodiment of the third embodiment will be described. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0577] In conventional systems, it was difficult to properly analyze an individual's strengths and emotions and generate specific action proposals based on them. In addition, there was a lack of means to provide specific action proposals for utilizing individual strengths and emotions in management, making it impossible to make the most of individual abilities and emotions.

[0578] The specific processing by the specific processing unit 290 of the data processing device 12 in the third embodiment is realized by the following means.

[0579] In this invention, the server includes a means for objectively judging the strengths of an individual, a means for loading the judgment result into a natural language processing tool, a means for the natural language processing tool to output a specific action proposal based on the judgment result, a means for identifying the user's emotion, an emotion engine for analyzing the emotion, and a means for the emotion engine to output a specific action proposal based on the emotion. This makes it possible to analyze an individual's strengths and emotions and generate a specific action proposal based thereon.

[0580] "Individual strengths" refer to the specific abilities or characteristics that an individual possesses, in which they excel compared to others.

[0581] "Objective means of judgment" refers to a method that eliminates subjective bias and evaluates an individual's strengths based on data and facts.

[0582] "Natural language processing tools" refers to software and algorithms that analyze, understand, and generate human language.

[0583] "Judgment results" refer to the results of an objective evaluation of an individual's strengths.

[0584] "Proposed actions" are specific actions or steps recommended for achieving a particular objective.

[0585] "User emotion" refers to the psychological state a user feels in response to a particular situation or stimulus.

[0586] An "emotion engine" refers to software or algorithms that analyze a user's emotions and generate appropriate action suggestions based on the results.

[0587] "Analyze" refers to examining data or information in detail to understand its structure and meaning.

[0588] "Management" refers to the process of planning, organizing, directing, and controlling resources to achieve organizational or project objectives.

[0589] The present invention is a system for analyzing an individual's strengths and emotions and generating specific action proposals based on the analysis. A specific embodiment of this system is described below.

[0590] Hardware and Software Used

[0591] Hardware: Servers, terminals

[0592] Software: Natural language processing tools, emotion engines, strengths assessment tools

[0593] Program Processing

[0594] Identify user strengths

[0595] A user identifies his or her strengths using the strengths determination tool. The user answers a series of questions to the tool and receives the results. For example, if a user identifies "strategic thinking" as a strength, the results are generated by the strengths determination tool.

[0596] Generate action suggestions to leverage strengths

[0597] The server uses a natural language processing tool to analyze the results of the strengths assessment tool. Based on the analysis results, the server generates specific action suggestions to utilize the user's strengths. For example, for a user whose strength is "strategic thinking," the server suggests that the user be involved in strategy formulation and business planning.

[0598] Identify user sentiment

[0599] A user inputs their emotions using the emotion engine. The user selects or inputs their current emotional state to the emotion engine. For example, if the user is feeling "happy," that emotion is analyzed by the emotion engine.

[0600] Generate action suggestions to leverage emotions

[0601] The server uses an emotion engine to analyze the user's emotions. Based on the analysis results, the server generates specific action suggestions to utilize the user's emotions. For example, if the user is feeling "joy," the server suggests an action to share that joy. Also, if the user is feeling "anger," the server suggests a dialogue or discussion to resolve the anger.

[0602] Examples

[0603] Examples of using the results of the Strengths Assessment Tool

[0604] User: Use the Strengths Identification Tool to identify "Strategic Thinking" as a strength.

[0605] Server: Uses natural language processing tools to generate action suggestions to leverage "strategic thinking."

[0606] Proposal: Engage users in strategic and business planning activities.

[0607] Example of using the results of the emotion engine

[0608] User: Uses the emotion engine to input that he / she is feeling "happy."

[0609] Server: Uses an emotion engine to generate action suggestions for sharing "joy."

[0610] Suggestion: Suggest specific actions that users can take to share their joy.

[0611] Examples of prompt statements

[0612] Prompts that utilize the results of the Strengths Assessment Tool

[0613] If your user's strength is "strategic thinking," generate specific suggestions for action to leverage that strength.

[0614] Prompts that leverage the results of the emotion engine

[0615] If the user is experiencing “joy”, generate specific action suggestions to share that joy.

[0616] The flow of the identification process in the third embodiment will be described with reference to FIG.

[0617] Step 1:

[0618] Users use the strengths assessment tool to identify their strengths.

[0619] Input: The user answers a series of questions to the strengths assessment tool.

[0620] Data processing: The strengths assessment tool analyzes the user's responses and evaluates the strengths using a specific algorithm.

[0621] Output: User strengths (e.g. "strategic thinking") are identified.

[0622] What happens: Users answer questions and the tool analyzes the answers to identify strengths.

[0623] Step 2:

[0624] The server loads the results of the strengths assessment tool into a natural language processing tool.

[0625] Input: Results of the strengths determination tool (user's strengths).

[0626] Data processing: Natural language processing tools analyze the results of the strengths assessment tool.

[0627] Output: Specific action suggestions to leverage strengths.

[0628] Specific operation: The server inputs the results of the strengths assessment tool into a natural language processing tool, which analyzes the results and generates action suggestions.

[0629] Step 3:

[0630] The server uses natural language processing tools to generate action suggestions based on the results of the strengths assessment tool.

[0631] Input: Results of the strengths determination tool (user's strengths).

[0632] Data processing: Natural language processing tools analyze strengths and generate action suggestions based on them.

[0633] Output: Specific suggested actions to leverage the user's strengths.

[0634] Specific action: The server suggests to users whose strength is "strategic thinking" that they be involved in strategic planning and business planning tasks.

[0635] Step 4:

[0636] The user inputs his / her own emotions using the emotion engine.

[0637] Input: The user selects or inputs their current emotional state to the emotion engine.

[0638] Data processing: The emotion engine analyzes user input to identify their emotional state.

[0639] Output: The user's emotional state (e.g. "delighted").

[0640] Specific operation: The user inputs an emotion such as "joy" or "anger" into the emotion engine, and the engine analyzes the emotion.

[0641] Step 5:

[0642] The server uses an emotion engine to analyze the user's emotions.

[0643] Input: The user's emotional state (e.g., "happy").

[0644] Data processing: The emotion engine analyzes the emotional state and generates action suggestions based on it.

[0645] Output: Specific action suggestions for leveraging emotions.

[0646] Specific operation: The server proposes actions to share joy for users who feel "happy." It also proposes dialogue or discussion to resolve anger for users who feel "anger."

[0647] (Application example 3)

[0648] Next, a description will be given of Application Example 3 of Form Example 3. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0649] Conventional systems have had the problem that it is difficult to improve work efficiency and personnel allocation that fully utilizes the strengths and emotions of individuals. In particular, when it comes to collaboration between machines and humans working in factories, there is a need to propose optimal work allocation and collaboration methods that take into account the strengths and emotions of each individual, but there has been a lack of concrete means to achieve this.

[0650] The identification process by the identification processing unit 290 of the data processing device 12 in the application example 3 is realized by the following means. In this invention, the server includes a means for objectively judging the strengths of individuals, a means for loading the judgment result into a natural language processing tool, a means for the natural language processing tool to output a specific action proposal based on the judgment result, a means for an emotion engine to analyze the user's emotions, a means for the emotion engine to output a specific action proposal based on the emotions, and a means for analyzing the strengths and emotions of machines and people working in a factory in real time and proposing optimal work placements and collaboration methods. This makes it possible to improve personnel placement and work efficiency by making the most of individual strengths and emotions.

[0651] A "means for objectively assessing an individual's strengths" is a device or method for objectively evaluating an individual's abilities and characteristics and obtaining the results as data.

[0652] A "natural language processing tool" is software or algorithms for analyzing, understanding, and generating natural language.

[0653] The "means for reading the judgment results into a natural language processing tool" refers to a device or method for inputting the results of evaluating an individual's strengths into a natural language processing tool.

[0654] The "means for outputting specific action suggestions" refers to a device or method that allows a natural language processing tool to suggest specific actions or countermeasures based on the analysis results.

[0655] An "emotion engine" is software or algorithms that analyze a user's emotions and obtain their emotional state as data.

[0656] The "means for analyzing user emotions" refers to a device or method for analyzing a user's emotions using an emotion engine and acquiring the results as data.

[0657] A "means for analyzing in real time the strengths and emotions of machines and humans working in a factory" refers to a device or method for analyzing in real time the capabilities and emotions of machines and humans operating in a factory and obtaining the results as data.

[0658] The "means for proposing optimal work layout and collaboration method" refers to a device or method for proposing optimal work layout within a factory and an optimal collaboration method between humans and machines based on the analysis results.

[0659] A system for implementing the present invention is configured as follows.

[0660] First, the server has a means to objectively judge the strengths of individuals. This means is a device or method for evaluating an individual's abilities and characteristics and acquiring the results as data. For example, software for analyzing the results of questionnaires or tests corresponds to this.

[0661] Next, the server has a means for loading the judgment results into a natural language processing tool. This means is a device or method for inputting the results of evaluating the strengths of individuals into the natural language processing tool. Specifically, this corresponds to an API that passes the evaluation results obtained from the database to the natural language processing tool.

[0662] Furthermore, the server has a means for the natural language processing tool to output a specific action proposal based on the judgment result. This means is an apparatus or method for the natural language processing tool to propose a specific action or countermeasure based on the analysis result. For example, the action proposal is generated using an OpenAI API.

[0663] The server also has a means for the emotion engine to analyze the user's emotions. This means is a device or method for analyzing the user's emotions using the emotion engine and acquiring the results as data. Specifically, this corresponds to emotion recognition software.

[0664] Furthermore, the server has a means for the emotion engine to output a specific action proposal based on the emotion. This means is a device or method for the emotion engine to propose a specific action or countermeasure based on the analysis result. For example, if the user feels happy, an action to share the emotion is proposed.

[0665] Finally, the server has the means to analyze the strengths and emotions of the machines and humans working in the factory in real time and propose optimal work placement and collaboration methods. This means is a device or method for analyzing the capabilities and emotions of the machines and humans working in the factory in real time and acquiring the results as data. Specifically, this corresponds to software that collects and analyzes data using sensors and cameras.

[0666] For example, if a user named “Taro” has strengths in “precision work” and “strategic thinking” and feels “joy,” the system might generate the following behavioral suggestions:

[0667] Example prompt:

[0668] Your users' strengths are precision work and strategic thinking, and their emotion is pleasure. Generate optimal action suggestions.

[0669] An example of the action suggestions generated:

[0670] Put Taro in precision assembly work, involve him in strategic project planning, and use team-building activities to share Taro's joy and boost morale across the team.

[0671] In this way, it is possible to improve personnel allocation and work efficiency by making the most of each individual's strengths and emotions.

[0672] The flow of the specific process in the application example 3 will be described with reference to FIG.

[0673] Step 1:

[0674] The server collects data to objectively judge the strengths of individuals. Specifically, it retrieves the results of questionnaires and tests from a database. This data includes information about the abilities and characteristics of individuals. The input is the result data of the questionnaires and tests, and the output is evaluation data that indicates the strengths of individuals.

[0675] Step 2:

[0676] The server inputs the collected evaluation data into a natural language processing tool. Specifically, the evaluation data is passed to the natural language processing tool via an API. Through this process, the natural language processing tool analyzes and understands the evaluation data. The input is the evaluation data, and the output is the analysis results.

[0677] Step 3:

[0678] The server generates specific action suggestions based on the analysis results generated by the natural language processing tool. Specifically, it uses a generative AI model to input a prompt sentence and generate action suggestions. The input is the analysis result and the prompt sentence, and the output is a specific action suggestion.

[0679] Step 4:

[0680] The server uses an emotion engine to analyze the user's emotions. Specifically, it uses sensors and cameras to collect the user's facial and voice data, which it then analyzes with emotion recognition software. The input is facial and voice data, and the output is emotion data.

[0681] Step 5:

[0682] The server generates specific action suggestions based on the emotion data generated by the emotion engine. Specifically, the emotion data is input into a natural language processing tool, and action suggestions are generated using a generative AI model. The input is the emotion data and a prompt sentence, and the output is a specific action suggestion.

[0683] Step 6:

[0684] The server analyzes the strengths and emotions of the machines and people working in the factory in real time. Specifically, it collects data using sensors and cameras and analyzes it in real time using analysis software. The input is data from the sensors and cameras, and the output is real-time strengths and emotion data.

[0685] Step 7:

[0686] The server proposes optimal work arrangements and collaboration methods based on real-time strengths and emotion data. Specifically, a generative AI model is used to input prompt sentences and generate optimal work arrangements and collaboration methods. The inputs are real-time strengths and emotion data and prompt sentences, and the output is a proposal for optimal work arrangements and collaboration methods.

[0687] In this way, the server can improve staffing and work efficiency by making the most of each individual's strengths and emotions.

[0688] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires a voice indicating a user input for the result of the specific processing. The control unit 46A transmits the voice data indicating the user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the voice data.

[0689] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (registered trademark) (Internet search<URL: https: / / openai.com / blog / chatgpt> ) and other generation AIs. The data generation model 58 is obtained by making a neural network perform deep learning. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating a voice, text data indicating a text, and image data indicating an image is input. The data generation model 58 performs inference on the input inference data according to the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0690] Another example of generative AI is Gemini (registered trademark) (Internet search <url: https: gemini.google.com ?hl="ja">) are mentioned.

[0691] In the above embodiment, the specific process is performed by the data processing device 12. However, the technology of the present disclosure is not limited to this. The specific process may be performed by the smart device 14.

[0692] This may be done.

[0693] [Second embodiment]

[0694] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0695] 3, the data processing system 210 includes the data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0696] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a wide area network (WAN) and / or a local area network (LAN).

[0697] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, and the camera 42 are also connected to the bus 52.

[0698] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs the voice according to instructions from the processor 46.

[0699] Camera 42 is a small digital camera equipped with an optical system including a lens, an aperture, and a shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (e.g., an imaging range defined by an angle of view equivalent to the width of the field of vision of an average healthy person).

[0700] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for transmitting and receiving various types of information between the processor 46 and the processor 28 via the network 54. The transmission and reception of various types of information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is performed in a secure state.

[0701] Fig. 4 shows an example of main functions of the data processing device 12 and the smart glasses 214. As shown in Fig. 4, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0702] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32, and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0703] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0704] In the smart glasses 214, the reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50, and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0705] Next, the specific processing by the specific processing unit 290 of the data processing device 12 will be described.

[0706] "Example 1"

[0707] In one embodiment of the present invention, a strengths judgment tool is used as a tool for objectively judging the strengths of an individual. This strengths judgment tool analyzes an individual's behavioral tendencies and thought patterns, and outputs the results as a report. The report is in text format, and its contents can be analyzed by a natural language processing tool.

[0708] "Example 2"

[0709] Next, the natural language processing tool reads the report output from the strengths assessment tool. The natural language processing tool analyzes the contents of the report and generates specific action suggestions based on the results. Specifically, based on the contents of the report, it suggests what actions an individual should take to make the most of their strengths.

[0710] "Example 3"

[0711] In addition, the natural language processing tool generates specific action suggestions to utilize the results of the strengths assessment tool for management. For example, if an individual's strength is "strategic thinking," it will suggest that the individual be involved in strategic planning and business planning. This will enable management to allocate personnel in a way that makes the most of each individual's strengths.

[0712] The process flow of each embodiment will be described below.

[0713] "Example 1"

[0714] Step 1: Each individual uses a strengths assessment tool to determine their own strengths. This tool analyzes the individual's behavioral tendencies and thought patterns, and outputs the results in a report.

[0715] Step 2: A natural language processing tool reads the report output from the strengths assessment tool. The tool analyzes the contents of the report and generates specific action suggestions based on the results.

[0716] "Example 2"

[0717] Step 1: Each individual uses a strengths assessment tool to determine their own strengths. This tool analyzes the individual's behavioral tendencies and thought patterns, and outputs the results in a report.

[0718] Step 2: A natural language processing tool reads the report output from the strengths assessment tool. The tool analyzes the contents of the report and generates specific action suggestions based on the results.

[0719] Step 3: The natural language processing tool also generates specific action suggestions to utilize the results of the strengths assessment tool in management. For example, if an individual's strength is "strategic thinking," it is suggested that the individual be involved in strategic planning and business planning. "Form example 3"

[0720] Step 1: Each individual uses a strengths assessment tool to determine their own strengths. This tool analyzes the individual's behavioral tendencies and thought patterns, and outputs the results in a report.

[0721] Step 2: A natural language processing tool reads the report output from the strengths assessment tool. The tool analyzes the contents of the report and generates specific action suggestions based on the results.

[0722] Step 3: The natural language processing tool also generates specific action suggestions to utilize the results of the strengths assessment tool for management. For example, if an individual's strength is "strategic thinking," it suggests involving the individual in strategic planning and business planning.

[0723] Example 1

[0724] Next, a description will be given of Example 1 of Form Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal".

[0725] Conventional systems for assessing individual strengths often relied on subjective evaluations, making it difficult to make objective judgments. In addition, the results of the assessments could not be linked to specific action proposals, making it difficult to utilize the systems for personal self-improvement and management. Furthermore, there was also an issue of inconsistency in the process from data collection to report generation, making it difficult to operate efficiently.

[0726] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0727] In this invention, the server includes a means for objectively judging the strengths of an individual, a means for loading the judgment result into a natural language processing tool, a means for the natural language processing tool to output a specific action proposal based on the judgment result, a means for collecting data input by a user, a means for preprocessing the collected data, a means for extracting features from the preprocessed data, a means for analyzing the strengths of an individual based on the extracted features, a means for generating a report of the analysis result, and a means for delivering the generated report to a user. This makes it possible to objectively judge the strengths of an individual and to propose a specific action based on the result. In addition, since the process from collecting data to generating the report is performed consistently, efficient operation is possible.

[0728] "Means for objectively assessing an individual's strengths" is a method for analyzing an individual's behavioral tendencies and thought patterns, eliminating subjective elements, and objectively evaluating strengths.

[0729] A "natural language processing tool" is software for analyzing text data and extracting meaning, emotions, keywords, etc.

[0730] "Means for outputting specific action suggestions" refers to a method for presenting specific actions or improvement measures that an individual should take based on the analysis results.

[0731] The "means for collecting data input by the user" refers to a method for collecting data such as self-assessments and behavioral records provided by the user.

[0732] "Means for pre-processing collected data" refers to a method for removing unnecessary information from collected data and converting the data into a form suitable for analysis.

[0733] A "means for extracting features from preprocessed data" is a method for finding important keywords and patterns from the preprocessed data.

[0734] The "means for analyzing the strengths of an individual based on the extracted characteristics" is a method for evaluating and analyzing the strengths of an individual using the extracted characteristics.

[0735] "Means for generating a report based on the analysis results" refers to a method for compiling the analysis results and outputting them as a text-format report.

[0736] The "means for delivering the generated report to the user" refers to a method for transmitting the generated report to the user's terminal so that the user can check it.

[0737] The present invention is a system for objectively determining the strengths of an individual and proposing specific actions based on the results. A specific embodiment of this system will be described below.

[0738] System Configuration

[0739] Hardware and Software

[0740] This system consists of three main components: a server, a terminal, and a user. The server collects data, pre-processes it, extracts features, analyzes strengths, and generates and distributes reports. The terminal inputs data from users and receives reports. Users input data such as self-evaluations and behavioral records.

[0741] The server uses the following software:

[0742] Natural language processing tools: NLTK, spaCy

[0743] Machine learning models: scikit-learn, TensorFlow

[0744] Program Processing

[0745] Data collection

[0746] The user inputs self-evaluation and behavior records from the terminal. For example, the user inputs a prompt sentence such as "I am good at working in a team and often demonstrate leadership." The terminal transmits this input data to the server.

[0747] Data Preprocessing

[0748] The server converts the received data into text format and filters out unnecessary information. Specifically, it removes HTML tags and special characters to make the text clean. For example, I am good at working in a team and often demonstrate leadership skills. " Remove HTML tags from the data.

[0749] Feature Extraction

[0750] The server uses natural language processing tools (e.g., NLTK and spaCy) to extract features from text data. Specifically, it performs keyword extraction and sentiment analysis. For example, it extracts keywords such as "teamwork," "leadership," and "problem-solving ability."

[0751] Strengths Analysis

[0752] The server analyzes the individual's strengths based on the extracted features. Here, a machine learning model (e.g., scikit-learn or TensorFlow) is used. For example, to determine that "leadership is a strength," the server calculates a score by comparing it with past data.

[0753] Generate reports

[0754] The server generates a report based on the analysis results and outputs it in text format. Specifically, it generates a report with the content such as "Your strengths are leadership and problem-solving ability."

[0755] Report distribution

[0756] The server sends the generated report to the user's terminal. The user can check the report on the terminal. For example, the user can receive a report such as "Your strengths are leadership and problem-solving ability" and can objectively understand his or her strengths.

[0757] Examples

[0758] When a user enters self-assessment data, a prompt sentence like the following is input to the generative AI model.

[0759] Example prompt:

[0760] "I work well in teams and often demonstrate leadership skills. I am also a good problem solver and enjoy tackling complex challenges."

[0761] Based on this prompt, the server collects data, pre-processes it, extracts features, analyzes strengths, and generates and distributes reports, allowing users to objectively evaluate their strengths and receive specific suggestions for action based on the results.

[0762] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0763] Step 1: Data collection

[0764] The user inputs self-evaluation and behavior records from the terminal. For example, the user inputs a prompt sentence such as "I am good at working in a team and often demonstrate leadership." The terminal sends this input data to the server. The input data is in text format, and the server receives it.

[0765] Step 2: Data Preprocessing

[0766] The server preprocesses the received text data. Specifically, it removes HTML tags and special characters to make the text clean. For example, I am good at working in a team and often demonstrate leadership skills. " HTML tags are removed from the data. The preprocessed text data is output.

[0767] Step 3: Feature Extraction

[0768] The server extracts features from the preprocessed text data. It uses natural language processing tools (e.g., NLTK and spaCy) to extract keywords and perform sentiment analysis. For example, it extracts keywords such as "teamwork," "leadership," and "problem-solving ability." The extracted feature data is output.

[0769] Step 4: Strengths analysis

[0770] The server analyzes the strengths of individuals based on the extracted feature data. Using a machine learning model (e.g., scikit-learn or TensorFlow), it compares the data with past data and calculates a score. For example, to determine that "leadership is a strength," the feature data is input into the model and a score is calculated. The analysis results are then output.

[0771] Step 5: Generate reports

[0772] The server generates a report based on the analysis results. It creates a text report with the content such as "Your strengths are leadership and problem-solving ability." The generated report is output.

[0773] Step 6: Report distribution

[0774] The server sends the generated report to the user's terminal. The user can check the report on the terminal. For example, the user can receive a report such as "Your strengths are leadership and problem-solving ability" and can objectively understand his or her strengths.

[0775] (Application example 1)

[0776] Next, a description will be given of Application Example 1 of Form Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal".

[0777] In conventional factories, it was difficult to assign workers to tasks that fully utilize their strengths, making it difficult to achieve efficient work allocation. In addition, there was a lack of means to objectively evaluate the behavioral tendencies and thought patterns of each worker and to assign them optimal tasks based on that. This led to problems of reduced work efficiency and reduced motivation among workers.

[0778] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0779] In this invention, the server includes a means for objectively judging the strengths of individuals, a means for inputting the judgment result into a natural language processing tool, a means for the natural language processing tool to output a specific action proposal based on the judgment result, and a means for allocating workers to optimal tasks based on the action proposal, thereby enabling efficient task allocation that makes the most of the strengths of workers.

[0780] "Individual strengths" are the specific abilities and characteristics that each worker possesses, and are factors that contribute to work efficiency and results.

[0781] "Means of objective judgment" are methods or tools for collecting data on an individual's behavioral tendencies and thought patterns and evaluating them without subjectivity.

[0782] A "natural language processing tool" is software or algorithms that analyze text data and understand its meaning and intent.

[0783] "Judgment results" are the data or information obtained after an objective evaluation of an individual's strengths.

[0784] The "specific action suggestions" are specific actions or work contents that are recommended to the worker based on the judgment results.

[0785] A "means for allocating workers to optimal tasks" is a method or system for allocating workers to the most suitable tasks or roles, taking into account their strengths and characteristics.

[0786] The system for carrying out the present invention is for objectively determining the strengths of individuals and allocating workers to the most suitable tasks based on the results. A specific embodiment of this system will be described below.

[0787] System Configuration

[0788] The system consists of the following main components:

[0789] 1. A means to objectively assess an individual's strengths: This is software that collects and analyzes data on the behavioral tendencies and thought patterns of workers. Specifically, it uses sensors and log data to record and analyze the behavior of workers.

[0790] 2. Natural Language Processing Tools: These tools are used to analyze the collected data and identify individual strengths. They use Python’s NLTK library and scikit-learn to analyze text data.

[0791] 3. Means for outputting specific action suggestions: Based on the judgment results obtained by the natural language processing tool, specific action suggestions are generated for the worker. Using the generative AI model, a prompt sentence is input and the optimal action suggestion is generated.

[0792] 4. Means for allocating workers to optimal tasks: This is an algorithm for allocating workers to optimal tasks based on action suggestions. Using KMeans clustering, we classify workers into appropriate groups and allocate tasks optimally.

[0793] Program processing explanation

[0794] The server first collects data on the behavior of workers. This is done using sensor and log data. The collected data is then analyzed using natural language processing tools. Specifically, the NLTK library is used to tokenize the text data and perform TF-IDF vectorization. After that, the workers are classified into clusters using scikit-learn's KMeans clustering.

[0795] Next, a generative AI model is used to generate specific action suggestions based on the clustering results. A prompt is input, and the generative AI model outputs optimal action suggestions. Based on these action suggestions, workers are assigned to optimal tasks.

[0796] Examples

[0797] For example, let's say you have the following worker data:

[0798] Analyze the behavioral trends of workers and propose optimal work placement. Below is the worker data.

[0799] [

[0800] {"name": "A", "behavior": "Works quickly. Good problem-solving skills."},

[0801] {"name": "B", "behavior": "Good at detailed work. Works carefully."},

[0802] {"name": "C", "behavior": "Emphasis on teamwork. Excellent communication skills."}

[0803] ]

[0804] Based on this data, the system identifies the strengths of each worker and suggests optimal task allocations. For example, Worker A, who works quickly, can be assigned to tasks that require emergency response. Worker B, who excels at detailed work, can be assigned to precision work. Worker C, who values ​​teamwork, can be assigned as a team leader.

[0805] In this way, the system makes the most of workers' strengths and achieves efficient work allocation.

[0806] The flow of the specific process in the application example 1 will be described with reference to FIG.

[0807] Step 1:

[0808] The server collects the worker's behavior data. Specifically, it records the worker's behavior using sensors and log data. The inputs include the worker's behavior log and sensor data. These data are stored in a database for subsequent analysis. The output is the collected behavior data.

[0809] Step 2:

[0810] The server preprocesses the collected behavioral data. Specifically, it uses a natural language processing tool (NLTK library) to tokenize the text data, remove non-alphabetical characters, and remove stop words. The input is the behavioral data collected in step 1. The output is the preprocessed text data.

[0811] Step 3:

[0812] The server converts the preprocessed text data into a TF-IDF vector. Specifically, it uses scikit-learn's TfidfVectorizer to convert the text data into a numerical vector. The input is the text data preprocessed in step 2. The output is a TF-IDF vector.

[0813] Step 4:

[0814] The server performs clustering using the TF-IDF vectors. Specifically, it uses scikit-learn's KMeans clustering algorithm to classify workers into multiple clusters. The input is the TF-IDF vector obtained in step 3. The output is the cluster information for each worker.

[0815] Step 5:

[0816] The server generates specific action suggestions based on the clustering results. Specifically, the generative AI model is used to input a prompt sentence and generate optimal action suggestions. The input is the cluster information and the prompt sentence. The output is the generated action suggestions.

[0817] Step 6:

[0818] The server assigns workers to optimal tasks based on the generated action proposals. Specifically, it analyzes the action proposals and executes an algorithm to assign optimal tasks to each worker. The input is the action proposals generated in step 5. The output is optimal task assignment information.

[0819] Step 7:

[0820] The server notifies the workers of the optimal work allocation information. Specifically, it uses a notification system to notify each worker of the new work allocation. The input is the optimal work allocation information obtained in step 6. The output is the notification to the workers.

[0821] Example 2

[0822] Next, a description will be given of Example 2 of the embodiment 2. In the following description, the data processing device 12 is referred to as a "server" and the smart glasses 214 are referred to as a "terminal".

[0823] Although conventional systems can objectively judge an individual's strengths, it is difficult to generate suggestions for linking those strengths to concrete actions. In addition, it is not clear how the generated action suggestions can be used for individual self-improvement and management, so the actual effect is limited.

[0824] The identification process by the identification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes a means for objectively judging the strengths of an individual, a means for loading the judgment result into a natural language processing tool, a means for the natural language processing tool to generate a specific action proposal based on the judgment result, and a means for outputting the action proposal. This makes it possible to automatically generate a specific action proposal for making the most of an individual's strengths, and to effectively utilize the action proposal for the individual's self-improvement and management.

[0825] "Individual strengths" refer to the specific abilities or characteristics that an individual possesses, in which they excel compared to others.

[0826] "Judgment objectively" means making an evaluation based on data and facts, without being influenced by subjectivity or emotion.

[0827] A "natural language processing tool" refers to software and algorithms for analyzing text data and understanding its meaning and structure.

[0828] "Judgment results" refer to the results of an objective evaluation of an individual's strengths.

[0829] "Action suggestions" refer to specific actions that individuals can take to make the most of their strengths.

[0830] "Outputting" refers to providing the generated information in a form usable by a user.

[0831] "Self-improvement" refers to the efforts and activities that an individual undertakes to improve his or her own abilities and knowledge.

[0832] "Management" refers to the operation and management of an organization or project.

[0833] The present invention is a system for objectively determining the strengths of an individual and generating specific action proposals based on the results of the determination. A specific embodiment of this system will be described below.

[0834] The server first collects data to objectively determine an individual's strengths. This data is obtained from various sources, such as survey results and performance evaluations. The server then analyzes this data to identify the individual's strengths.

[0835] The server then feeds the results of the identified strengths into a natural language processing tool. Specifically, the server uses spaCy, a Python natural language processing library, which is used to tokenize the text data and extract key keywords and phrases.

[0836] The server uses natural language processing tools to analyze the results of the judgment and generates specific action suggestions based on the results. For example, if the report states that "this individual has excellent team leadership," the server generates action suggestions such as "serve as a leader for team projects" and "regularly communicate with team members."

[0837] The generated action proposal is provided to the user by the server. Specifically, the action proposal is output in text format and can be viewed by the user. This allows the user to take specific actions to make the most of their strengths.

[0838] As a concrete example, here is a prompt that a user can enter into a generative AI model:

[0839] "Please suggest what action individuals should take based on this report."

[0840] Examples of specific prompts include the following:

[0841] The report states:

[0842] Strengths: Team Leadership

[0843] Details: This individual has excellent team building skills and excels at project management.

[0844] Action suggestion:

[0845] Lead a team project

[0846] Communicate with team members regularly

[0847] Regularly review project progress

[0848] In this way, the server analyzes the contents of the report and generates and outputs specific action proposals for individuals to make the most of their strengths, which can be effectively used for self-improvement and management of individuals.

[0849] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0850] Step 1: Load the report

[0851] The server reads the report output from the strengths assessment tool. Specifically, the server specifies the file path where the report is saved, opens the file, and obtains the contents. The file path of the report is required as input, and the contents of the report are obtained in text format as output.

[0852] Step 2: Analyze the report

[0853] The server analyzes the report content using natural language processing tools. Specifically, the server uses spaCy, a Python natural language processing library, to tokenize the report text and extract important keywords and phrases. The input is the report text, and the output is the extracted keywords and phrases.

[0854] Step 3: Generate action suggestions

[0855] The server generates specific action suggestions based on the analysis results. Specifically, the server suggests actions that individuals can take to make the most of their strengths based on the extracted keywords and phrases. For example, if the keyword "team leadership" is extracted, the server generates action suggestions such as "serve as a leader in a team project." The input requires the extracted keywords and phrases, and the output is a specific action suggestion.

[0856] Step 4: Output action suggestions

[0857] The server provides the generated action proposal to the user. Specifically, the server outputs the action proposal in a text format so that the user can view it. The generated action proposal is required as an input, and the action proposal in a format viewable by the user is obtained as an output.

[0858] In this way, the server analyzes the contents of the report and generates and outputs specific action proposals for individuals to make the most of their strengths, which can be effectively used for self-improvement and management of individuals.

[0859] (Application example 2)

[0860] Next, a description will be given of Application Example 2 of Form Example 2. In the following description, the data processing device 12 will be referred to as a "server", and the smart glasses 214 will be referred to as a "terminal".

[0861] Conventional factory robot systems have difficulty automatically generating specific action suggestions to maximize production efficiency. In addition, there was no system that could objectively determine an individual's strengths and output specific action suggestions based on them. As a result, it was not possible to effectively support the improvement of production efficiency or the self-improvement of individuals.

[0862] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0863] In this invention, the server includes a means for objectively judging the strengths of individuals, a means for loading the judgment result into a natural language processing tool, a means for the natural language processing tool to output a specific action proposal based on the judgment result, a means for analyzing a production report in the factory with the natural language processing tool, and a means for proposing what action each robot should take to maximize production efficiency. This makes it possible to effectively support the improvement of production efficiency and the self-improvement of individuals.

[0864] "Individual strengths" refer to the specific abilities or characteristics that an individual possesses, in which they excel compared to others.

[0865] "Judgment objectively" means making an evaluation based on facts and data, without being influenced by subjectivity or emotion.

[0866] "Natural language processing tools" refer to technology and software that allows computers to analyze and understand human language.

[0867] An "action proposal" is a proposal that outlines specific actions or steps to be taken to achieve a particular goal.

[0868] An "in-factory production report" refers to a document that records the status and results of production activities in a factory.

[0869] "Analyze" refers to examining data or information in detail to clarify its structure and meaning.

[0870] "Production efficiency" refers to the ratio of production results obtained to the resources input, and is an indicator of efficient production activities.

[0871] A "robot" refers to a mechanical device that performs work automatically, especially those used in production activities in factories and other places.

[0872] To "propose" means to present a solution or plan of action for a specific problem or challenge.

[0873] A system for carrying out the present invention has the following configuration: A server includes means for objectively judging the strengths of individuals, means for loading the judgment results into a natural language processing tool, means for the natural language processing tool to output specific action suggestions based on the judgment results, means for analyzing production reports within the factory with the natural language processing tool, and means for proposing what actions each robot should take to maximize production efficiency.

[0874] Program processing explanation

[0875] The server first collects data to objectively judge an individual's strengths. This data includes the individual's past performance, evaluations, skill sets, etc. Next, the collected data is loaded into a natural language processing tool to analyze the individual's strengths. For this analysis, a Japanese natural language processing model is loaded using the spacy library, and a summary is generated using the transformers library pipeline.

[0876] Based on the analysis, natural language processing tools suggest how individuals can take action to make the most of their strengths, using generative AI models to generate specific action suggestions.

[0877] In addition, the system uses natural language processing tools to analyze production reports from within the factory and proposes what actions each robot should take to maximize production efficiency. This analysis involves examining the contents of the reports in detail and processing and calculating data to clarify their structure and meaning.

[0878] Examples

[0879] As a concrete example, we use a report on production efficiency within a factory as input. Below is an example of a prompt sentence to be input to the generative AI model.

[0880] This is a report on production efficiency in a factory. In the current production line, a bottleneck occurs in a specific process. In order to eliminate this bottleneck, it is necessary to optimize the operation of the robots. Specifically, production efficiency can be improved by adjusting the timing of material supply and the operating speed of each robot.

[0881] Taking this prompt as input, the server generates the following action suggestions:

[0882] Adjust the timing of material supply.

[0883] Adjust the movement speed of each robot.

[0884] This makes it possible to provide specific action suggestions for factory robots to maximize production efficiency.

[0885] The flow of the specific process in the application example 2 will be described with reference to FIG.

[0886] Step 1:

[0887] The server collects data to objectively determine an individual's strengths.

[0888] Inputs: Data such as an individual’s past performance, ratings, and skill sets.

[0889] Output: The collected data.

[0890] Specific operation: The server retrieves data on individual performance and evaluations from databases and external systems and stores this in an internal database.

[0891] Step 2:

[0892] The server loads the collected data into a natural language processing tool to analyze each individual's strengths.

[0893] Input: Collected data.

[0894] Output: Analysis of individual strengths.

[0895] How it works: The server loads a Japanese natural language processing model using the spacy library and analyzes the collected data. The analysis results are output as text data showing the individual's strengths.

[0896] Step 3:

[0897] The server generates specific action suggestions based on the analysis results.

[0898] Input: Personal strengths analysis results.

[0899] Output: Specific suggestions for action.

[0900] Specific Actions: The server uses a generative AI model to generate action suggestions that show an individual what actions to take to best utilize their strengths.

[0901] Step 4:

[0902] The server analyzes production reports from within the factory using natural language processing tools.

[0903] Input: In-factory production report.

[0904] Output: Analysis results of production report.

[0905] Specific operation: The server uses the transformers library pipeline to generate a summary of the production report and perform detailed analysis of the report contents.

[0906] Step 5:

[0907] Based on the analysis results, the server suggests what actions each robot should take to maximize production efficiency.

[0908] Input: Analysis results of production report.

[0909] Output: Specific suggestions for action.

[0910] Specific actions: The server uses the generative AI model to generate specific action suggestions to improve production efficiency, for example, making suggestions on adjusting the timing of material supply or the speed of robot movements.

[0911] Step 6:

[0912] The server provides the generated action suggestions to the user.

[0913] Input: Specific proposals for action.

[0914] Output: Action suggestions provided to the user.

[0915] Specific operation: The server sends the generated action proposal to the user's terminal so that the user can review it.

[0916] Example 3

[0917] Next, a third embodiment of the third embodiment will be described. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal".

[0918] In conventional personnel allocation systems, it was difficult to fully utilize the strengths of individuals, and personnel were often not assigned to appropriate tasks. In addition, there was a lack of means to objectively judge individuals' strengths and generate specific action proposals based on them, making it difficult for management to make effective personnel allocations.

[0919] The identification process by the identification processing unit 290 of the data processing device 12 in the third embodiment is realized by the following means. In this invention, the server includes a means for objectively judging the strengths of individuals, a means for loading the judgment result into a natural language processing tool, a means for the natural language processing tool to input a prompt sentence into a generative AI model based on the judgment result and output a specific action proposal, and a means for providing the action proposal to management. This enables personnel allocation that makes the most of individual strengths.

[0920] "Individual strengths" are specific abilities or characteristics that an individual possesses, and are the factors that enable them to perform better than others in a task or activity.

[0921] "Means of objective judgment" are methods or tools for accurately evaluating an individual's strengths based on data and evaluation criteria, without relying on subjectivity.

[0922] A "natural language processing tool" is software or algorithms for analyzing text data and understanding its meaning.

[0923] A "generative AI model" is an artificial intelligence model that generates new information or suggestions based on input data.

[0924] A "prompt" is an instruction or question input to a generative AI model that triggers the model to generate an appropriate output.

[0925] "Action suggestions" are suggestions that provide specific actions or work instructions based on an individual's strengths and analysis results.

[0926] "Management" refers to the people or departments responsible for running and managing an organization or team.

[0927] The present invention is a system for objectively determining the strengths of an individual and generating specific action proposals based on the results. A specific embodiment of this system is described below.

[0928] Hardware and Software Used

[0929] Hardware: Servers, terminals (PCs and smartphones)

[0930] Software: Generative AI models (e.g. GPT-4), natural language processing tools (e.g. SpaCy)

[0931] System Overview

[0932] The system starts with the user accessing the strengths assessment tool using a terminal and inputting information on self-evaluation and work performance. The server receives the data sent by the user and analyzes it using natural language processing tools. Based on the analysis results, it inputs prompt sentences into the generative AI model to generate specific action suggestions. Finally, the server provides the generated action suggestions to management.

[0933] Examples

[0934] 1. The user accesses the strengths assessment tool and enters information

[0935] The user uses the terminal to access the web page or application of the strengths assessment tool, answers questions about self-evaluation and work performance, and inputs the required information.

[0936] Example: A user answers "Strategic planning" to the question "What do you do best?"

[0937] 2. The server receives and analyzes the user input data

[0938] The server receives the data sent by the user and analyzes it using a natural language processing tool (e.g. SpaCy). As a result of the analysis, the user's strengths are identified.

[0939] Example: The server parses the answer "strategic planning" and identifies the user's strength as "strategic thinking."

[0940] 3. The server inputs a prompt sentence into the generative AI model based on the analysis results and generates action suggestions.

[0941] Based on the analysis results, the server inputs a prompt sentence into a generative AI model (e.g., GPT-4), which then generates a specific action suggestion based on the prompt sentence.

[0942] Example: The server inputs the prompt sentence "This individual's strength is strategic thinking. Please suggest what kind of work this individual should be involved in to utilize this strength" to the generative AI model, and the generative AI model generates an action suggestion such as "Suggest involving this individual in strategic planning and business planning."

[0943] 4. The server provides the generated action proposals to the management.

[0944] The server provides the generated action proposals to management, who then receives the proposals and assigns personnel to maximize the use of each individual's strengths.

[0945] Example: The server sends an action proposal to management, such as "I suggest that this individual be involved in strategic planning and business planning," and management assigns the relevant individual to the appropriate task based on that proposal.

[0946] In this way, the system supports personnel allocation that makes the most of each individual's strengths. The flow of the identification process in the third embodiment will be described with reference to FIG.

[0947] Step 1:

[0948] The user accesses the strengths assessment tool and inputs information.

[0949] Specific actions: The user uses the terminal to access the strengths assessment tool web page or application. The user answers questions about self-evaluation and work performance and enters the required information.

[0950] Input: Information about the user's self-assessment and job performance.

[0951] Output: The user's input data.

[0952] Step 2:

[0953] The server receives and analyzes the user's input data.

[0954] Specific operation: The server receives the data sent by the user and analyzes the data using a natural language processing tool (e.g. SpaCy). As a result of the analysis, the user's strengths are identified.

[0955] Input: Data entered by the user.

[0956] Output: Analysis results identifying user strengths.

[0957] Step 3:

[0958] Based on the analysis results, the server inputs prompt sentences into the generative AI model and generates action suggestions.

[0959] Specific action: Based on the analysis results, the server inputs a prompt sentence into the generative AI model (e.g. GPT-4). The generative AI model generates specific action suggestions based on the prompt sentence.

[0960] Input: Analysis result and prompt.

[0961] Output: Specific action suggestions from the generative AI model.

[0962] Step 4:

[0963] The server provides the generated action suggestions to the management.

[0964] Specific operation: The server provides the generated action proposals to management. Management receives the proposals and assigns personnel to make the most of each individual's strengths.

[0965] Input: Generated action suggestions.

[0966] Output: Action suggestions provided to management.

[0967] (Application example 3)

[0968] Next, a description will be given of Application Example 3 of Form Example 3. In the following description, the data processing device 12 will be referred to as a "server", and the smart glasses 214 will be referred to as a "terminal".

[0969] In conventional personnel allocation systems, the strengths of each worker could not be fully utilized, and optimal work allocation was often not performed. As a result, there were problems with reduced work efficiency and lack of improvement in productivity. In addition, there was a lack of means to objectively judge the strengths of workers and propose specific actions based on that, making it difficult for management to perform appropriate personnel allocation.

[0970] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 3 is realized by the following means.

[0971] In this invention, the server includes a means for objectively judging the strengths of individuals, a means for inputting the judgment result into a natural language processing tool, a means for the natural language processing tool to output a specific action proposal based on the judgment result, and a means for proposing an optimal task allocation for workers based on the action proposal, thereby enabling optimal task allocation that makes the most of the strengths of each worker.

[0972] "Individual strengths" refers to the unique abilities, skills, and areas of expertise that a particular individual possesses.

[0973] "Means of objective judgment" refers to a method of accurately evaluating an individual's strengths based on data and evaluation criteria, without relying on subjectivity.

[0974] "Natural language processing tools" refers to computer programs and algorithms that understand, analyze, and generate human language.

[0975] "Judgment results" refers to data and information obtained as a result of an objective evaluation of an individual's strengths.

[0976] "Specific action suggestions" refer to suggestions that specifically indicate what actions an individual should take based on the judgment results.

[0977] "Optimal worker allocation" refers to the allocation of workers to perform tasks most efficiently and effectively based on their strengths and capabilities.

[0978] A "server" refers to a computer system that processes and stores data on a network.

[0979] The system for carrying out the present invention objectively judges the strengths of individuals and proposes optimal work allocation based on the results. A specific embodiment of this system will be described below.

[0980] The server first collects data to objectively determine an individual's strengths. This data can come from a worker's past performance, skill assessments, feedback, etc. The server then loads this data into a natural language processing tool that uses OpenAI's API and includes a generative AI model to analyze individual strengths.

[0981] The natural language processing tool analyzes the collected data and identifies the strengths of the individual. For example, if a worker is good at precision work, "precision work" is identified as the worker's strength. The result of this judgment is sent to the server.

[0982] Next, the server generates specific action suggestions based on the results of this judgment. For example, a suggestion is generated to assign a worker who is good at precision work to the assembly of precision equipment. This action suggestion is used to determine the optimal task allocation of workers.

[0983] As a concrete example, by inputting the following prompt sentences into a generative AI model, we can obtain optimal work placement suggestions:

[0984] Worker strengths data:

[0985] Person A: Precision work

[0986] Person B: Physical strength

[0987] Person C: Strategic thinking

[0988] Work content and required strengths:

[0989] Precision equipment assembly: precision work

[0990] Lifting heavy objects: Physical strength

[0991] Production Line Optimization: Strategic Thinking

[0992] Based on the above data, please suggest the optimal work arrangement.

[0993] By inputting this prompt into a generative AI model, the server can obtain optimal work placement suggestions, resulting in efficient work placement that makes the most of the strengths of each worker.

[0994] The hardware used is a computer system that processes and stores data over a network, and the software uses Python and OpenAI APIs, which makes it possible to analyze the strengths of each worker and propose optimal work placement.

[0995] The flow of the specific process in the application example 3 will be described with reference to FIG.

[0996] Step 1:

[0997] The server collects data to objectively judge the strengths of workers. As input, it receives data such as the worker's past performance, skill evaluation, and feedback, and stores it in a database. As output, it obtains the collected data.

[0998] Step 2:

[0999] The server loads the collected data into a natural language processing tool. As input, it uses the data collected in step 1 and sends the data to the natural language processing tool. As output, it gets the data in a format that the natural language processing tool can parse.

[1000] Step 3:

[1001] The natural language processing tool analyzes the input data and identifies the strengths of the workers. As input, it uses the data obtained in step 2 and performs analysis using a generative AI model. As output, data is obtained in which the strengths of each worker are identified.

[1002] Step 4:

[1003] The server generates specific action suggestions based on the strengths data obtained from the natural language processing tool. As input, it uses the strengths data obtained in step 3 and inputs prompt sentences into the generative AI model. As output, it obtains specific action suggestions for each worker.

[1004] Step 5:

[1005] The server proposes an optimal task placement for workers based on the generated action proposals. As input, it uses the action proposals obtained in step 4 and matches the tasks with the required strengths. As output, it obtains an optimal task placement proposal.

[1006] Step 6:

[1007] The server notifies the workers and management of the optimal work placement proposal. As input, it uses the work placement proposal obtained in step 5 and sends information to the workers and management via the notification system. As output, the workers and management receive the optimal work placement proposal.

[1008] In addition, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1009] "Example 1"

[1010] In one embodiment of the present invention, a strengths assessment tool such as Gallup's StrengthsFinder is used as a means for objectively assessing an individual's strengths. This tool analyzes an individual's behavioral tendencies and thought patterns, and outputs the results as a report. Next, a natural language processing tool reads this report. This tool analyzes the contents of the report and generates specific action suggestions based on the results. Furthermore, an emotion engine recognizes the user's emotions and generates specific action suggestions based on the emotions. Specifically, if the user is feeling joy, an action that will increase the joy is suggested. Also, if the user is feeling sad, an action that will reduce the sadness is suggested.

[1011] "Example 2"

[1012] In another embodiment of the present invention, the emotion engine generates specific action suggestions based on the user's emotions to support personal self-improvement, such as when the user is excited, action suggestions are made to leverage the excitement to learn new skills, and when the user is depressed, action suggestions are made to overcome depression.

[1013] "Example 3"

[1014] In yet another embodiment of the present invention, the emotion engine generates specific action suggestions to utilize the user's emotions for emotion management, for example, if the user is feeling happy, it suggests an action to share the happiness, and if the user is feeling angry, it suggests a dialogue or discussion to resolve the anger.

[1015] The process flow of each embodiment will be described below.

[1016] "Example 1"

[1017] Step 1: Users assess their own strengths using a strengths-determining tool such as Gallup's StrengthsFinder.

[1018] Step 2: The strengths assessment tool analyzes the user's behavioral tendencies and thought patterns and outputs the results in a report.

[1019] Step 3: A natural language processing tool reads the report and analyzes its content.

[1020] Step 4: Natural language processing tools generate specific action suggestions based on the analysis results.

[1021] Step 5: The emotion engine recognizes the user's emotion.

[1022] Step 6: The emotion engine generates specific action suggestions based on the emotions it recognizes.

[1023] "Example 2"

[1024] Step 1: The emotion engine recognizes the user's emotion.

[1025] Step 2: Based on the emotions recognized by the emotion engine, specific action suggestions are generated to support the individual's self-improvement.

[1026] "Example 3"

[1027] Step 1: The emotion engine recognizes the user's emotion.

[1028] Step 2: Based on the emotions recognized by the emotion engine, specific action suggestions are generated for use in management.

[1029] Example 1

[1030] Next, a description will be given of Example 1 of Form Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal".

[1031] Conventional systems for assessing individual strengths lacked specific action suggestions that utilize the results of the strength assessment, which meant that users could not effectively utilize the results in self-improvement and management. In addition, the system did not take into account the user's emotions when proposing actions, which meant that appropriate support was not provided according to the user's emotional state.

[1032] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1033] In this invention, the server includes a means for objectively judging an individual's strengths, a means for loading the judgment result into a natural language processing tool, a means for the natural language processing tool to output a specific action proposal based on the judgment result, a means for recognizing the user's emotion using an emotion recognition engine, and a means for generating an action proposal according to the emotion based on the result of the emotion recognition engine. This makes it possible to propose a specific action that makes use of the user's strengths, and further to provide appropriate support according to the user's emotional state.

[1034] "Means for objectively assessing individual strengths" refers to tools or algorithms that analyze an individual's behavioral tendencies and thought patterns and identify their strengths based on the results.

[1035] A "natural language processing tool" is software or algorithms used to analyze text data and understand and process its content.

[1036] An "emotion recognition engine" is software or algorithms used to analyze a user's emotional state and identify those emotions.

[1037] The "means for outputting action suggestions" refers to a function or algorithm for suggesting specific actions to the user based on the analysis results.

[1038] A "means for generating action suggestions according to emotions" is a function or algorithm for taking into account the emotional state of the user and suggesting actions appropriate to those emotions.

[1039] This invention is a system that objectively judges the strengths of individuals and proposes specific actions based on the results. This system works in cooperation with a server, a terminal, and a user.

[1040] First, the user uses a terminal to input information about his / her own behavioral tendencies and thought patterns. This information is collected through questionnaires or self-evaluation sheets. The terminal then transmits the user's response data to a server.

[1041] The server uses the received user data to objectively determine the strengths of the individual. Specifically, it uses a strengths assessment tool such as Gallup's StrengthsFinder tool. The server inputs the user data into this tool and analyzes the individual's behavioral tendencies and thought patterns. The analysis results are generated as a report and saved in text format.

[1042] Next, the server passes the generated report to a natural language processing tool (e.g., Google Cloud Natural Language API) to analyze the content. The natural language processing tool analyzes the text data of the report and returns the results to the server. Based on the analysis results, the server generates specific action suggestions that utilize the user's strengths. For example, if the user's strength is "leadership," it will make specific action suggestions to demonstrate leadership.

[1043] Furthermore, the server recognizes the user's emotions using an emotion recognition engine (e.g., IBM Watson Tone Analyzer). The user's emotion data is obtained from input from the terminal and past behavioral history. The emotion recognition engine analyzes the user's emotional state and returns the results to the server. Based on the emotion analysis results, the server generates specific action suggestions according to the user's emotions. For example, if the user is feeling happy, the server suggests actions that will increase that happiness. Also, if the user is feeling sad, the server suggests actions that will reduce that sadness.

[1044] As a concrete example, let us consider a case where the user is determined to have strengths in "leadership" and "empathy." The server generates the following action suggestions:

[1045] Demonstrate leadership by taking the lead in setting goals for your team.

[1046] Use your empathy and actively listen to your team members' opinions.

[1047] If the emotion engine recognizes the user's emotions and determines that the user is feeling happy, it will suggest the following actions:

[1048] Share success stories with your team to amplify the joy.

[1049] If the user is feeling sad, the following action suggestions are made:

[1050] To ease your grief, set aside time to talk with a trusted colleague.

[1051] Example prompt:

[1052] Analyze user strengths and generate specific action suggestions based on user behavioral tendencies and thought patterns. Consider user emotions and suggest actions to increase joy or reduce sadness.

[1053] In this way, a system is realized in which the server, terminal, and user work together to objectively judge an individual's strengths and provide specific suggestions for action.

[1054] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1055] Step 1:

[1056] The user uses the terminal to input information about his / her own behavioral tendencies and thought patterns. The input information is collected through questionnaires or self-evaluation sheets. The terminal transmits the user's response data to the server.

[1057] Input: Information about the user's behavioral tendencies and thought patterns

[1058] Output: User data sent to the server.

[1059] Specific operation: The user answers questions displayed on the device screen, and the device sends the data to the server.

[1060] Step 2:

[1061] The server uses the received user data to objectively judge the strengths of the individual. Specifically, it uses a strengths judgment tool. The server inputs the user data into this tool and analyzes the individual's behavioral tendencies and thought patterns.

[1062] Input: User data

[1063] Output: Analysis results from the strengths assessment tool

[1064] Specific operation: The server calls the API of the strengths assessment tool, sends user data, and receives the analysis results.

[1065] Step 3:

[1066] The server generates a report summarizing the user's strengths based on the analysis results obtained from the strengths assessment tool, and saves the report in text format.

[1067] Input: Analysis results of strengths assessment tool

[1068] Output: Text report

[1069] Specific operation: The server converts the analysis results into a text report and stores it in a database.

[1070] Step 4:

[1071] The server passes the generated report to a natural language processing tool for content analysis. The natural language processing tool analyzes the text data of the report and returns the results to the server.

[1072] Input: Text report

[1073] Output: Analysis results from natural language processing tools

[1074] Specific operation: The server sends the report's text data to a natural language processing tool and receives the analysis results.

[1075] Step 5:

[1076] The server generates specific action suggestions that utilize the user's strengths based on the analysis results obtained from the natural language processing tool.

[1077] Input: Analysis results of natural language processing tools

[1078] Output: Specific action suggestions

[1079] Specific operation: The server runs an algorithm to generate action suggestions based on the analysis results, and generates the action suggestions in text format.

[1080] Step 6:

[1081] The server uses an emotion recognition engine to recognize the user's emotions. The user's emotion data is obtained from input from the terminal and from the user's past behavior history.

[1082] Input: User emotion data

[1083] Output: Emotion analysis results by the emotion recognition engine

[1084] Specific operation: The user inputs his / her current emotion through the terminal, and the server sends the emotion data to the emotion recognition engine and receives the analysis results.

[1085] Step 7:

[1086] The server generates specific action suggestions according to the user's emotions based on the emotion analysis results obtained from the emotion recognition engine.

[1087] Input: Emotion analysis results from the emotion recognition engine

[1088] Output: Specific action suggestions based on emotions

[1089] Specific operation: The server runs an algorithm that generates action suggestions based on the results of emotion analysis. If the user is feeling happy, the server suggests actions that will increase that joy, and if the user is feeling sad, the server suggests actions that will reduce that sadness.

[1090] (Application example 1)

[1091] Next, a description will be given of Application Example 1 of Form Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal".

[1092] Conventional tools for determining individual strengths identify strengths by analyzing an individual's behavioral tendencies and thought patterns, but it is difficult to link the results to specific action suggestions. In addition, since action suggestions do not take into account the user's emotional state, there is a problem in that appropriate suggestions cannot be made according to the user's current emotions. Furthermore, there is a lack of concrete measures to personalize shopping experiences in physical stores.

[1093] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1094] In this invention, the server includes a means for objectively judging an individual's strengths, a means for loading the judgment result into a natural language processing tool, a means for the natural language processing tool to output a specific action proposal based on the judgment result, a means for recognizing a user's emotion, a means for generating an action proposal based on the emotion, and a means for proposing optimal products and services based on the user's strengths and emotional state. This makes it possible to propose specific actions according to the user's strengths and emotional state, thereby personalizing the shopping experience at a brick-and-mortar store.

[1095] "Means of objectively assessing an individual's strengths" refers to a method for analyzing an individual's behavioral tendencies and thought patterns and identifying that individual's strengths based on the results.

[1096] The "means for reading the judgment result into a natural language processing tool" refers to a means for inputting the result of judging an individual's strengths into a natural language processing tool.

[1097] "The means by which the natural language processing tool outputs specific action suggestions based on the judgment results" refers to the means by which the natural language processing tool analyzes the judgment results of an individual's strengths and generates specific action suggestions based thereon.

[1098] A "means for recognizing a user's emotion" is a means for detecting and recognizing a user's current emotional state.

[1099] The "means for generating action suggestions based on the emotion" refers to means for generating appropriate action suggestions based on the recognized emotional state of the user.

[1100] The "means for proposing optimal products and services based on the user's strengths and emotional state" refers to a means for proposing optimal products and services taking into account the user's strengths and current emotional state.

[1101] A system for implementing this invention includes means for objectively judging an individual's strengths, means for loading the judgment result into a natural language processing tool, means for the natural language processing tool to output specific action suggestions based on the judgment result, means for recognizing the user's emotions, means for generating action suggestions based on the emotions, and means for suggesting optimal products and services based on the user's strengths and emotional state.

[1102] Program processing explanation

[1103] Hardware and software used

[1104] Hardware: Smartphone

[1105] Software: Python, TextBlob, Transformers (Hugging Face)

[1106] Data processing and calculation

[1107] 1. A means of objectively assessing an individual's strengths: The server uses tools to analyze an individual's behavioral tendencies and thought patterns, and outputs the results as a report in JSON format.

[1108] 2. Means for inputting the judgment result into a natural language processing tool: The server inputs the generated report into a natural language processing tool (TextBlob) and performs text analysis.

[1109] 3. Means for the natural language processing tool to output specific action suggestions based on the judgment result: The natural language processing tool generates action suggestions based on the analysis result.

[1110] 4. Means for recognizing user's emotions: The server uses Hugging Face's Transformers to recognize the user's emotional state.

[1111] 5. Means for generating action suggestions based on the emotion: The server generates appropriate action suggestions based on the recognized emotional state.

[1112] 6. Means for suggesting optimal products and services based on the user's strengths and emotional state: The server suggests optimal products and services taking into account the user's strengths and emotional state.

[1113] Examples

[1114] When a user enters a physical store, the application installed on the smartphone automatically starts. The application analyzes the user's strengths and current emotional state, and if the user has a "positive emotion," for example, the application makes a suggestion such as "Try these products by utilizing your strengths."

[1115] Examples of prompt statements

[1116] Recommend the best products and services based on the user's strengths and emotional state. If the user is feeling positive, suggest products that play to their strengths, if they are feeling negative, suggest products to lift their mood.

[1117] The flow of the specific process in the application example 1 will be described with reference to FIG.

[1118] Step 1:

[1119] The server uses tools to analyze an individual's behavioral tendencies and thought patterns, and outputs the results as a report in JSON format. The input is an individual's behavioral data and thought pattern data, and the output is a report that identifies the individual's strengths. Specifically, the server collects behavioral data and applies an analysis algorithm to identify strengths.

[1120] Step 2:

[1121] The server inputs the generated report into a natural language processing tool (TextBlob) and performs text analysis. The input is the report generated in step 1, and the output is the analysis results. Specifically, the report text is read and sentiment analysis and keyword extraction are performed using TextBlob.

[1122] Step 3:

[1123] The natural language processing tool generates action suggestions based on the analysis results. The input is the analysis results obtained in step 2, and the output is specific action suggestions. Specifically, the tool applies an action suggestion algorithm based on the analysis results to generate action suggestions suitable for the user.

[1124] Step 4:

[1125] The server uses Hugging Face Transformers to recognize the user's emotional state. The input is text data that indicates the user's current emotion, and the output is the emotion recognition result. Specifically, the server inputs the user's text data into the Transformers and obtains emotion labels.

[1126] Step 5:

[1127] The server generates appropriate action suggestions based on the recognized emotional state. The input is the emotion recognition result obtained in step 4, and the output is the emotion-based action suggestions. Specifically, the server applies an action suggestion algorithm based on the emotion recognition result to generate action suggestions according to the user's emotions.

[1128] Step 6:

[1129] The server proposes optimal products and services taking into account the user's strengths and emotional state. The input is the action proposal obtained in step 3 and the action proposal based on the emotion obtained in step 5, and the output is the optimal product or service proposal. Specifically, the server integrates both proposals and selects and proposes the optimal product or service to the user.

[1130] Example 2

[1131] Next, a description will be given of Example 2 of the embodiment 2. In the following description, the data processing device 12 is referred to as a "server" and the smart glasses 214 are referred to as a "terminal".

[1132] Conventional systems can objectively judge an individual's strengths, but it is difficult to provide specific action suggestions to make the most of those strengths. It is also difficult to generate action suggestions based on the user's emotional state. This has led to the problem that effective support cannot be provided for individual self-improvement and management.

[1133] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1134] In this invention, the server includes a means for objectively judging the strengths of an individual, a means for loading the judgment result into a natural language processing tool, a means for the natural language processing tool to output a specific action proposal based on the judgment result, a means for collecting emotion data of a user, a means for analyzing the emotion data with an emotion analysis tool, and a means for the emotion analysis tool to output a specific action proposal based on the emotion data. This makes it possible to provide a specific action proposal based on an individual's strengths and emotional state.

[1135] An "objective means of assessing individual strengths" is a method or device for evaluating an individual's characteristics and capabilities and identifying their strengths based on objective criteria.

[1136] "Natural language processing tools" are software and algorithms that analyze text data and understand meaning and sentiment.

[1137] The "means for loading the judgment results into a natural language processing tool" refers to a method or device for inputting the results of judging an individual's strengths into a natural language processing tool.

[1138] The "means for outputting specific action suggestions" refers to a method or device for suggesting specific actions that an individual should take based on the analysis results.

[1139] A "means for collecting user emotional data" is a method or device for measuring a user's emotional state and collecting that data.

[1140] An "emotion analysis tool" is software or algorithms that analyze collected emotion data and identify a user's emotional state.

[1141] The "means for outputting specific action suggestions based on emotion data" refers to a method or device for suggesting specific actions that a user should take based on the results of an emotion analysis tool.

[1142] The present invention is a system for generating specific action suggestions based on an individual's strengths and emotional state. A specific embodiment of the system will be described below.

[1143] First, we generate a program for the system that combines natural language processing and sentiment analysis tools to generate specific action suggestions based on the user's strengths and emotions.

[1144] Hardware and Software Used

[1145] Server: Receives data, analyzes it, and generates action suggestions.

[1146] Terminal: Collects user emotion data.

[1147] Natural language processing tools: Text analysis tools such as Google Cloud Natural Language API.

[1148] Sentiment analysis tools: Sentiment analysis tools such as IBM Watson Tone Analyzer.

[1149] Generative AI models: Generative AI models such as OpenAI GPT-3.

[1150] Data processing and calculation

[1151] 1. Receive a report from the strengths assessment tool

[1152] The server receives the report output from the strengths assessment tool. The report is provided in JSON format, PDF format, etc.

[1153] 2. Analyze the report contents using natural language processing tools

[1154] The server uses the Google Cloud Natural Language API to analyze the report content. Specifically, the server sends the report's text data to the API and performs keyword extraction and sentiment analysis.

[1155] 3. Generate action suggestions based on the analysis results

[1156] Based on the analysis results, the server generates specific action suggestions using a generative AI model (e.g., OpenAI GPT-3). A prompt such as "Please generate specific action suggestions when leadership is a strength" is entered.

[1157] 4. Collect user sentiment data

[1158] The device collects the user's emotion data, which is obtained from the user's input or a wearable device (e.g., Fitbit or Apple Watch).

[1159] 5. Analyze the sentiment data with a sentiment analysis tool

[1160] The server uses IBM Watson Tone Analyzer to analyze the user's emotional data. Specifically, it sends the emotional data to an API to identify the user's emotional state (excited, depressed, etc.).

[1161] 6. Generate action suggestions based on emotions

[1162] The server uses a generative AI model to generate specific action suggestions based on the results of the emotion analysis tool. A prompt such as "If the user is excited, please generate action suggestions for learning a new skill" is entered.

[1163] Examples

[1164] 1. Examples of natural language processing tools

[1165] A user uses the strengths determination tool to generate a report.

[1166] The server receives the report and parses it using the Google Cloud Natural Language API.

[1167] The natural language processing tool analyzes the situation and finds that "leadership is a strength."

[1168] Natural language processing tools generate action suggestions such as "Lead the project."

[1169] 2. Specific examples of sentiment analysis tools

[1170] A user collects emotion data using a wearable device.

[1171] The server receives the emotion data and analyzes it using IBM Watson Tone Analyzer.

[1172] The sentiment analysis tool finds that the user is excited.

[1173] Sentiment analysis tools generate action suggestions such as "take an online course to learn a new skill."

[1174] Examples of prompt statements

[1175] "Analyze the Strengths Tool report and generate specific action suggestions where leadership is a strength."

[1176] "Generate action suggestions to learn a new skill if the user is excited about it."

[1177] In this way, the system generates specific action suggestions based on the user's strengths and emotions.

[1178] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1179] Step 1:

[1180] A server receives the report from the strengths determination tool.

[1181] Input: Report output from the strengths assessment tool (JSON, PDF, etc.).

[1182] How it works: The server downloads the report using an HTTP request.

[1183] Output: The downloaded report data.

[1184] Step 2:

[1185] The server analyzes the report contents using natural language processing tools.

[1186] Input: The downloaded report data.

[1187] How it works: The server uses the Google Cloud Natural Language API to send the report's text data to the API, which performs keyword extraction and sentiment analysis.

[1188] Output: Analysis results (keywords and sentiment information).

[1189] Step 3:

[1190] The server generates action suggestions based on the analysis results.

[1191] Input: Analysis results from natural language processing tools.

[1192] How it works: The server uses a generative AI model (e.g., OpenAI GPT-3) to generate specific action suggestions. Enter a prompt such as "Generate specific action suggestions if leadership is a strength."

[1193] Output: Generated action suggestions.

[1194] Step 4:

[1195] The terminal collects the user's emotion data.

[1196] Input: User emotion data (heart rate, activity level, etc.).

[1197] How it works: The device collects emotion data from a wearable device (e.g., Fitbit or Apple Watch).

[1198] Output: The collected emotion data.

[1199] Step 5:

[1200] The server analyzes the emotion data using an emotion analysis tool.

[1201] Input: Collected emotion data.

[1202] How it works: The server uses IBM Watson Tone Analyzer to send emotion data to the API to identify the user's emotional state (excited, depressed, etc.).

[1203] Output: Emotion analysis results.

[1204] Step 6:

[1205] The server generates action suggestions based on the emotions.

[1206] Input: Sentiment analysis results from the sentiment analysis tool.

[1207] How it works: The server uses the generative AI model to generate specific action suggestions, inputting a prompt such as "If the user is excited, generate action suggestions for learning a new skill."

[1208] Output: Generated action suggestions.

[1209] In this way, the system generates specific action suggestions based on the user's strengths and emotions.

[1210] (Application example 2)

[1211] Next, a description will be given of Application Example 2 of Form Example 2. In the following description, the data processing device 12 will be referred to as a "server", and the smart glasses 214 will be referred to as a "terminal".

[1212] Conventional systems can objectively judge an individual's strengths and suggest specific actions based on them, but they cannot suggest actions that take into account the individual's emotional state. Therefore, there is a need to provide appropriate action suggestions according to the individual's emotional state.

[1213] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1214] In this invention, the server includes a means for objectively judging the strengths of an individual, a means for loading the judgment result into a natural language processing tool, a means for the natural language processing tool to output a specific action proposal based on the judgment result, a means for analyzing the emotional state of the individual using an emotion analysis engine, and a means for generating a specific action proposal based on the emotional state. This makes it possible to make the most of the strengths of an individual and to propose an appropriate action according to the emotional state.

[1215] A "means for objectively assessing an individual's strengths" is a method or device for objectively evaluating an individual's abilities and characteristics and obtaining the results as data.

[1216] A "natural language processing tool" is software or algorithms used to analyze text data and understand and process its content.

[1217] The "means for outputting specific action suggestions" refers to a method or device for suggesting specific actions that an individual should take based on the analyzed data.

[1218] An "emotion analysis engine" is software or algorithms that analyze an individual's emotional state and obtain the results as data.

[1219] A "means for analyzing an individual's emotional state" is a method or device for analyzing an individual's emotions in real time and acquiring that state as data.

[1220] A "means for generating specific action suggestions based on emotional state" is a method or apparatus for suggesting specific actions for an individual to take based on the analyzed emotional data.

[1221] The system for carrying out the present invention objectively judges the strengths of an individual, proposes specific actions based on the results, and analyzes the emotional state of the individual to propose actions based on the emotions. A specific embodiment of this system will be described below.

[1222] Hardware and Software Used

[1223] Hardware: Smartphones, smart glasses

[1224] Software: Natural language processing tools (e.g. SpaCy), sentiment analysis engines (e.g. IBM Watson Tone Analyzer), generative AI models (e.g. OpenAI GPT-4)

[1225] Data processing and calculation

[1226] 1. A means to objectively assess individual strengths

[1227] The server acquires data for objectively judging the strengths of individuals. This data is collected, for example, from survey results and past performance data. Based on this data, the server uses a natural language processing tool (SpaCy) to analyze the strengths of individuals and generate evaluation results.

[1228] 2. Action suggestions using natural language processing tools

[1229] The server loads the acquired evaluation results into a natural language processing tool. The natural language processing tool analyzes the evaluation results and inputs a prompt sentence into a generative AI model (GPT-4) to generate specific action suggestions. For example, the following prompt sentence is used:

[1230] "Please suggest an approach that staff who are good at customer service should take when dealing with customers."

[1231] 3. Emotion analysis engine for analyzing emotional states

[1232] The server acquires the individual's emotional state in real time through a smartphone or smart glasses, and uses an emotion analysis engine (IBM Watson Tone Analyzer) to analyze the acquired emotional data and evaluate the individual's emotional state.

[1233] 4. Suggested actions based on emotional state

[1234] Based on the analyzed emotion data, the server inputs a prompt sentence into the generative AI model (GPT-4) to generate action suggestions according to the emotional state. For example, the following prompt sentence is used:

[1235] "Suggest actions to help staff feel refreshed if they are tired."

[1236] Examples

[1237] Proposal for utilizing strengths:

[1238] Staff A is good at serving customers. The server uses a natural language processing tool to suggest that "when a customer enters the store, greet them with a smile and listen carefully to their needs."

[1239] Emotion-based action suggestions:

[1240] If staff member B is tired, the server will use the sentiment analysis engine to suggest "take a 5-minute break and take a deep breath to refresh yourself."

[1241] In this way, a system can be realized that makes the most of an individual's strengths while suggesting appropriate actions based on the individual's emotional state.

[1242] The flow of the identification process in the application example 2 will be described with reference to FIG.

[1243] Step 1:

[1244] The server acquires data to objectively judge the strengths of individuals. Inputs include survey results and past performance data. Based on this data, a natural language processing tool (SpaCy) is used to analyze the strengths of individuals and generate evaluation results. The output is an evaluation result showing the strengths of each individual.

[1245] Step 2:

[1246] The server loads the acquired evaluation results into a natural language processing tool. The input includes the evaluation results generated in step 1. The natural language processing tool analyzes the evaluation results and inputs prompt sentences into a generative AI model (GPT-4) to generate specific action suggestions. The output is specific action suggestions based on the individual's strengths.

[1247] Step 3:

[1248] The server acquires the emotional state of an individual in real time through a smartphone or smart glasses. The input includes the user's emotional data. Using an emotion analysis engine (IBM Watson Tone Analyzer), the acquired emotional data is analyzed and the individual's emotional state is evaluated. The output is an evaluation result indicating the individual's emotional state.

[1249] Step 4:

[1250] Based on the analyzed emotion data, the server inputs a prompt sentence into the generative AI model (GPT-4) to generate action suggestions according to the emotional state. The input includes the evaluation result of the emotional state generated in step 3. The generative AI model generates specific action suggestions based on the emotional state. The output is a specific action suggestion according to the emotional state.

[1251] Step 5:

[1252] The terminal presents the specific action suggestions received from the server to the user. The input includes the action suggestions generated in steps 2 and 4. The terminal presents these action suggestions to the user visually or audibly. The output is the specific action suggestions received by the user.

[1253] In this way, a system can be realized that makes the most of an individual's strengths while suggesting appropriate actions based on the individual's emotional state.

[1254] Example 3

[1255] Next, a third embodiment of the third embodiment will be described. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal".

[1256] In conventional systems, it was difficult to properly analyze an individual's strengths and emotions and generate specific action proposals based on them. In addition, there was a lack of means to provide specific action proposals for utilizing individual strengths and emotions in management, making it impossible to make the most of individual abilities and emotions.

[1257] The specific processing by the specific processing unit 290 of the data processing device 12 in the third embodiment is realized by the following means.

[1258] In this invention, the server includes a means for objectively judging the strengths of an individual, a means for loading the judgment result into a natural language processing tool, a means for the natural language processing tool to output a specific action proposal based on the judgment result, a means for identifying the user's emotion, an emotion engine for analyzing the emotion, and a means for the emotion engine to output a specific action proposal based on the emotion. This makes it possible to analyze an individual's strengths and emotions and generate a specific action proposal based thereon.

[1259] "Individual strengths" refer to the specific abilities or characteristics that an individual possesses, in which they excel compared to others.

[1260] "Objective means of judgment" refers to a method that eliminates subjective bias and evaluates an individual's strengths based on data and facts.

[1261] "Natural language processing tools" refers to software and algorithms that analyze, understand, and generate human language.

[1262] "Judgment results" refer to the results of an objective evaluation of an individual's strengths.

[1263] "Proposed actions" are specific actions or steps recommended for achieving a particular objective.

[1264] "User emotion" refers to the psychological state a user feels in response to a particular situation or stimulus.

[1265] An "emotion engine" refers to software or algorithms that analyze a user's emotions and generate appropriate action suggestions based on the results.

[1266] "Analyze" refers to examining data or information in detail to understand its structure and meaning.

[1267] "Management" refers to the process of planning, organizing, directing, and controlling resources to achieve organizational or project objectives.

[1268] The present invention is a system for analyzing an individual's strengths and emotions and generating specific action proposals based on the analysis. A specific embodiment of this system is described below.

[1269] Hardware and Software Used

[1270] Hardware: Servers, terminals

[1271] Software: Natural language processing tools, emotion engines, strengths assessment tools

[1272] Program Processing

[1273] Identify user strengths

[1274] A user identifies his or her strengths using the strengths determination tool. The user answers a series of questions to the tool and receives the results. For example, if a user identifies "strategic thinking" as a strength, the results are generated by the strengths determination tool.

[1275] Generate action suggestions to leverage strengths

[1276] The server uses a natural language processing tool to analyze the results of the strengths assessment tool. Based on the analysis results, the server generates specific action suggestions to utilize the user's strengths. For example, for a user whose strength is "strategic thinking," the server suggests that the user be involved in strategy formulation and business planning.

[1277] Identify user sentiment

[1278] A user inputs their emotions using the emotion engine. The user selects or inputs their current emotional state to the emotion engine. For example, if the user is feeling "happy," that emotion is analyzed by the emotion engine.

[1279] Generate action suggestions to leverage emotions

[1280] The server uses an emotion engine to analyze the user's emotions. Based on the analysis results, the server generates specific action suggestions to utilize the user's emotions. For example, if the user is feeling "joy," the server suggests an action to share that joy. Also, if the user is feeling "anger," the server suggests a dialogue or discussion to resolve the anger.

[1281] Examples

[1282] Examples of using the results of the Strengths Assessment Tool

[1283] User: Use the Strengths Identification Tool to identify "Strategic Thinking" as a strength.

[1284] Server: Uses natural language processing tools to generate action suggestions to leverage "strategic thinking."

[1285] Proposal: Engage users in strategic and business planning activities.

[1286] Example of using the results of the emotion engine

[1287] User: Uses the emotion engine to input that he / she is feeling "happy."

[1288] Server: Uses an emotion engine to generate action suggestions for sharing "joy."

[1289] Suggestion: Suggest specific actions that users can take to share their joy.

[1290] Examples of prompt statements

[1291] Prompts that utilize the results of the Strengths Assessment Tool

[1292] If your user's strength is "strategic thinking," generate specific suggestions for action to leverage that strength.

[1293] Prompts that leverage the results of the emotion engine

[1294] If the user is experiencing “joy”, generate specific action suggestions to share that joy.

[1295] The flow of the identification process in the third embodiment will be described with reference to FIG.

[1296] Step 1:

[1297] Users use the strengths assessment tool to identify their strengths.

[1298] Input: The user answers a series of questions to the strengths assessment tool.

[1299] Data processing: The strengths assessment tool analyzes the user's responses and evaluates the strengths using a specific algorithm.

[1300] Output: User strengths (e.g. "strategic thinking") are identified.

[1301] What happens: Users answer questions and the tool analyzes the answers to identify strengths.

[1302] Step 2:

[1303] The server loads the results of the strengths assessment tool into a natural language processing tool.

[1304] Input: Results of the strengths determination tool (user's strengths).

[1305] Data processing: Natural language processing tools analyze the results of the strengths assessment tool.

[1306] Output: Specific action suggestions to leverage strengths.

[1307] Specific operation: The server inputs the results of the strengths assessment tool into a natural language processing tool, which analyzes the results and generates action suggestions.

[1308] Step 3:

[1309] The server uses natural language processing tools to generate action suggestions based on the results of the strengths assessment tool.

[1310] Input: Results of the strengths determination tool (user's strengths).

[1311] Data processing: Natural language processing tools analyze strengths and generate action suggestions based on them.

[1312] Output: Specific suggested actions to leverage the user's strengths.

[1313] Specific action: The server suggests to users whose strength is "strategic thinking" that they be involved in strategic planning and business planning tasks.

[1314] Step 4:

[1315] The user inputs his / her own emotions using the emotion engine.

[1316] Input: The user selects or inputs their current emotional state to the emotion engine.

[1317] Data processing: The emotion engine analyzes user input to identify their emotional state.

[1318] Output: The user's emotional state (e.g. "delighted").

[1319] Specific operation: The user inputs an emotion such as "joy" or "anger" into the emotion engine, and the engine analyzes the emotion.

[1320] Step 5:

[1321] The server uses an emotion engine to analyze the user's emotions.

[1322] Input: The user's emotional state (e.g., "happy").

[1323] Data processing: The emotion engine analyzes the emotional state and generates action suggestions based on it.

[1324] Output: Specific action suggestions for leveraging emotions.

[1325] Specific operation: The server proposes actions to share joy for users who feel "happy." It also proposes dialogue or discussion to resolve anger for users who feel "anger."

[1326] (Application example 3)

[1327] Next, a description will be given of Application Example 3 of Form Example 3. In the following description, the data processing device 12 will be referred to as a "server", and the smart glasses 214 will be referred to as a "terminal".

[1328] Conventional systems have had the problem that it is difficult to improve work efficiency and personnel allocation that fully utilizes the strengths and emotions of individuals. In particular, when it comes to collaboration between machines and humans working in factories, there is a need to propose optimal work allocation and collaboration methods that take into account the strengths and emotions of each individual, but there has been a lack of concrete means to achieve this.

[1329] The identification process by the identification processing unit 290 of the data processing device 12 in the application example 3 is realized by the following means. In this invention, the server includes a means for objectively judging the strengths of individuals, a means for loading the judgment result into a natural language processing tool, a means for the natural language processing tool to output a specific action proposal based on the judgment result, a means for an emotion engine to analyze the user's emotions, a means for the emotion engine to output a specific action proposal based on the emotions, and a means for analyzing the strengths and emotions of machines and people working in a factory in real time and proposing optimal work placements and collaboration methods. This makes it possible to improve personnel placement and work efficiency by making the most of individual strengths and emotions.

[1330] A "means for objectively assessing an individual's strengths" is a device or method for objectively evaluating an individual's abilities and characteristics and obtaining the results as data.

[1331] A "natural language processing tool" is software or algorithms for analyzing, understanding, and generating natural language.

[1332] The "means for reading the judgment results into a natural language processing tool" refers to a device or method for inputting the results of evaluating an individual's strengths into a natural language processing tool.

[1333] The "means for outputting specific action suggestions" refers to a device or method that allows a natural language processing tool to suggest specific actions or countermeasures based on the analysis results.

[1334] An "emotion engine" is software or algorithms that analyze a user's emotions and obtain their emotional state as data.

[1335] The "means for analyzing user emotions" refers to a device or method for analyzing a user's emotions using an emotion engine and acquiring the results as data.

[1336] A "means for analyzing in real time the strengths and emotions of machines and humans working in a factory" refers to a device or method for analyzing in real time the capabilities and emotions of machines and humans operating in a factory and obtaining the results as data.

[1337] The "means for proposing optimal work layout and collaboration method" refers to a device or method for proposing optimal work layout within a factory and an optimal collaboration method between humans and machines based on the analysis results.

[1338] A system for implementing the present invention is configured as follows.

[1339] First, the server has a means to objectively judge the strengths of individuals. This means is a device or method for evaluating an individual's abilities and characteristics and acquiring the results as data. For example, software for analyzing the results of questionnaires or tests corresponds to this.

[1340] Next, the server has a means for loading the judgment results into a natural language processing tool. This means is a device or method for inputting the results of evaluating the strengths of individuals into the natural language processing tool. Specifically, this corresponds to an API that passes the evaluation results obtained from the database to the natural language processing tool.

[1341] Furthermore, the server has a means for the natural language processing tool to output a specific action proposal based on the judgment result. This means is an apparatus or method for the natural language processing tool to propose a specific action or countermeasure based on the analysis result. For example, the action proposal is generated using an OpenAI API.

[1342] The server also has a means for the emotion engine to analyze the user's emotions. This means is a device or method for analyzing the user's emotions using the emotion engine and acquiring the results as data. Specifically, this corresponds to emotion recognition software.

[1343] Furthermore, the server has a means for the emotion engine to output a specific action proposal based on the emotion. This means is a device or method for the emotion engine to propose a specific action or countermeasure based on the analysis result. For example, if the user feels happy, an action to share the emotion is proposed.

[1344] Finally, the server has the means to analyze the strengths and emotions of the machines and humans working in the factory in real time and propose optimal work placement and collaboration methods. This means is a device or method for analyzing the capabilities and emotions of the machines and humans working in the factory in real time and acquiring the results as data. Specifically, this corresponds to software that collects and analyzes data using sensors and cameras.

[1345] For example, if a user named “Taro” has strengths in “precision work” and “strategic thinking” and feels “joy,” the system might generate the following behavioral suggestions:

[1346] Example prompt:

[1347] Your users' strengths are precision work and strategic thinking, and their emotion is pleasure. Generate optimal action suggestions.

[1348] An example of the action suggestions generated:

[1349] Put Taro in precision assembly work, involve him in strategic project planning, and use team-building activities to share Taro's joy and boost morale across the team.

[1350] In this way, it is possible to improve personnel allocation and work efficiency by making the most of each individual's strengths and emotions.

[1351] The flow of the specific process in the application example 3 will be described with reference to FIG.

[1352] Step 1:

[1353] The server collects data to objectively judge the strengths of individuals. Specifically, it retrieves the results of questionnaires and tests from a database. This data includes information about the abilities and characteristics of individuals. The input is the result data of the questionnaires and tests, and the output is evaluation data that indicates the strengths of individuals.

[1354] Step 2:

[1355] The server inputs the collected evaluation data into a natural language processing tool. Specifically, the evaluation data is passed to the natural language processing tool via an API. Through this process, the natural language processing tool analyzes and understands the evaluation data. The input is the evaluation data, and the output is the analysis results.

[1356] Step 3:

[1357] The server generates specific action suggestions based on the analysis results generated by the natural language processing tool. Specifically, it uses a generative AI model to input a prompt sentence and generate action suggestions. The input is the analysis result and the prompt sentence, and the output is a specific action suggestion.

[1358] Step 4:

[1359] The server uses an emotion engine to analyze the user's emotions. Specifically, it uses sensors and cameras to collect the user's facial and voice data, which it then analyzes with emotion recognition software. The input is facial and voice data, and the output is emotion data.

[1360] Step 5:

[1361] The server generates specific action suggestions based on the emotion data generated by the emotion engine. Specifically, the emotion data is input into a natural language processing tool, and action suggestions are generated using a generative AI model. The input is the emotion data and a prompt sentence, and the output is a specific action suggestion.

[1362] Step 6:

[1363] The server analyzes the strengths and emotions of the machines and people working in the factory in real time. Specifically, it collects data using sensors and cameras and analyzes it in real time using analysis software. The input is data from the sensors and cameras, and the output is real-time strengths and emotion data.

[1364] Step 7:

[1365] The server proposes optimal work arrangements and collaboration methods based on real-time strengths and emotion data. Specifically, a generative AI model is used to input prompt sentences and generate optimal work arrangements and collaboration methods. The inputs are real-time strengths and emotion data and prompt sentences, and the output is a proposal for optimal work arrangements and collaboration methods.

[1366] In this way, the server can improve staffing and work efficiency by making the most of each individual's strengths and emotions.

[1367] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires a voice indicating a user input for the result of the specific processing. The control unit 46A transmits the voice data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the voice data.

[1368] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ) and other generation AIs. The data generation model 58 is obtained by making a neural network perform deep learning. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating a voice, text data indicating a text, and image data indicating an image is input. The data generation model 58 performs inference on the input inference data according to the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1369] Another example of generative AI is Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) are mentioned.

[1370] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the smart glasses 214.

[1371] [Third embodiment]

[1372] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[1373] 5, the data processing system 310 includes the data processing device 12 and a headset type terminal 314. An example of the data processing device 12 is a server.

[1374] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a wide area network (WAN) and / or a local area network (LAN).

[1375] The headset type terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a display 343. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the display 343 are also connected to the bus 52.

[1376] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs the voice according to instructions from the processor 46.

[1377] The camera 42 is a small digital camera equipped with an optical system including a lens, an aperture, and a shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[1378] For example, an imaging range defined by an angle of view equivalent to the width of the visual field of a typical healthy person is imaged.

[1379] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for transmitting and receiving various types of information between the processor 46 and the processor 28 via the network 54. The transmission and reception of various types of information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is performed in a secure state.

[1380] Fig. 6 shows an example of main functions of the data processing device 12 and the headset type terminal 314. As shown in Fig. 6, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[1381] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32, and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[1382] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1383] In the headset type terminal 314, the reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50, and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1384] Next, the specific processing by the specific processing unit 290 of the data processing device 12 will be described.

[1385] "Example 1"

[1386] In one embodiment of the present invention, a strengths judgment tool is used as a tool for objectively judging the strengths of an individual. This strengths judgment tool analyzes an individual's behavioral tendencies and thought patterns, and outputs the results as a report. The report is in text format, and its contents can be analyzed by a natural language processing tool.

[1387] "Example 2"

[1388] Next, the natural language processing tool reads the report output from the strengths assessment tool. The natural language processing tool analyzes the contents of the report and generates specific action suggestions based on the results. Specifically, based on the contents of the report, it suggests what actions an individual should take to make the most of their strengths.

[1389] "Example 3"

[1390] In addition, the natural language processing tool generates specific action suggestions to utilize the results of the strengths assessment tool for management. For example, if an individual's strength is "strategic thinking," it will suggest that the individual be involved in strategic planning and business planning. This will enable management to allocate personnel in a way that makes the most of each individual's strengths.

[1391] The process flow of each embodiment will be described below.

[1392] "Example 1"

[1393] Step 1: Each individual uses a strengths assessment tool to determine their own strengths. This tool analyzes the individual's behavioral tendencies and thought patterns, and outputs the results in a report.

[1394] Step 2: A natural language processing tool reads the report output from the strengths assessment tool. The tool analyzes the contents of the report and generates specific action suggestions based on the results.

[1395] "Example 2"

[1396] Step 1: Each individual uses a strengths assessment tool to determine their own strengths. This tool analyzes the individual's behavioral tendencies and thought patterns, and outputs the results in a report.

[1397] Step 2: A natural language processing tool reads the report output from the strengths assessment tool. The tool analyzes the contents of the report and generates specific action suggestions based on the results.

[1398] Step 3: The natural language processing tool also generates specific action suggestions to utilize the results of the strengths assessment tool in management. For example, if an individual's strength is "strategic thinking," it is suggested that the individual be involved in strategic planning and business planning. "Form example 3"

[1399] Step 1: Each individual uses a strengths assessment tool to determine their own strengths. This tool analyzes the individual's behavioral tendencies and thought patterns, and outputs the results in a report.

[1400] Step 2: A natural language processing tool reads the report output from the strengths assessment tool. The tool analyzes the contents of the report and generates specific action suggestions based on the results.

[1401] Step 3: The natural language processing tool also generates specific action suggestions to utilize the results of the strengths assessment tool for management. For example, if an individual's strength is "strategic thinking," it suggests involving the individual in strategic planning and business planning.

[1402] Example 1

[1403] Next, a description will be given of Example 1 of the embodiment 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal".

[1404] Conventional systems for assessing individual strengths often relied on subjective evaluations, making it difficult to make objective judgments. In addition, the results of the assessments could not be linked to specific action proposals, making it difficult to utilize the systems for personal self-improvement and management. Furthermore, there was also an issue of inconsistency in the process from data collection to report generation, making it difficult to operate efficiently.

[1405] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1406] In this invention, the server includes a means for objectively judging the strengths of an individual, a means for loading the judgment result into a natural language processing tool, a means for the natural language processing tool to output a specific action proposal based on the judgment result, a means for collecting data input by a user, a means for preprocessing the collected data, a means for extracting features from the preprocessed data, a means for analyzing the strengths of an individual based on the extracted features, a means for generating a report of the analysis result, and a means for delivering the generated report to a user. This makes it possible to objectively judge the strengths of an individual and to propose a specific action based on the result. In addition, since the process from collecting data to generating the report is performed consistently, efficient operation is possible.

[1407] "Means for objectively assessing an individual's strengths" is a method for analyzing an individual's behavioral tendencies and thought patterns, eliminating subjective elements, and objectively evaluating strengths.

[1408] A "natural language processing tool" is software for analyzing text data and extracting meaning, emotions, keywords, etc.

[1409] "Means for outputting specific action suggestions" refers to a method for presenting specific actions or improvement measures that an individual should take based on the analysis results.

[1410] The "means for collecting data input by the user" refers to a method for collecting data such as self-assessments and behavioral records provided by the user.

[1411] "Means for pre-processing collected data" refers to a method for removing unnecessary information from collected data and converting the data into a form suitable for analysis.

[1412] A "means for extracting features from preprocessed data" is a method for finding important keywords and patterns from the preprocessed data.

[1413] The "means for analyzing the strengths of an individual based on the extracted characteristics" is a method for evaluating and analyzing the strengths of an individual using the extracted characteristics.

[1414] "Means for generating a report based on the analysis results" refers to a method for compiling the analysis results and outputting them as a text-format report.

[1415] The "means for delivering the generated report to the user" refers to a method for transmitting the generated report to the user's terminal so that the user can check it.

[1416] The present invention is a system for objectively determining the strengths of an individual and proposing specific actions based on the results. A specific embodiment of this system will be described below.

[1417] System Configuration

[1418] Hardware and Software

[1419] This system consists of three main components: a server, a terminal, and a user. The server collects data, pre-processes it, extracts features, analyzes strengths, and generates and distributes reports. The terminal inputs data from users and receives reports. Users input data such as self-evaluations and behavioral records.

[1420] The server uses the following software:

[1421] Natural language processing tools: NLTK, spaCy

[1422] Machine learning models: scikit-learn, TensorFlow

[1423] Program Processing

[1424] Data collection

[1425] The user inputs self-evaluation and behavior records from the terminal. For example, the user inputs a prompt sentence such as "I am good at working in a team and often demonstrate leadership." The terminal transmits this input data to the server.

[1426] Data Preprocessing

[1427] The server converts the received data into text format and filters out unnecessary information. Specifically, it removes HTML tags and special characters to make the text clean. For example, I am good at working in a team and often demonstrate leadership skills. " Remove HTML tags from the data.

[1428] Feature Extraction

[1429] The server uses natural language processing tools (e.g., NLTK and spaCy) to extract features from text data. Specifically, it performs keyword extraction and sentiment analysis. For example, it extracts keywords such as "teamwork," "leadership," and "problem-solving ability."

[1430] Strengths Analysis

[1431] The server analyzes the individual's strengths based on the extracted features. Here, a machine learning model (e.g., scikit-learn or TensorFlow) is used. For example, to determine that "leadership is a strength," a score is calculated by comparing with past data.

[1432] Generate reports

[1433] The server generates a report based on the analysis results and outputs it in text format. Specifically, it generates a report with the content such as "Your strengths are leadership and problem-solving ability."

[1434] Report distribution

[1435] The server sends the generated report to the user's terminal. The user can check the report on the terminal. For example, the user can receive a report such as "Your strengths are leadership and problem-solving ability" and can objectively understand his or her strengths.

[1436] Examples

[1437] When a user enters self-assessment data, a prompt sentence like the following is input to the generative AI model.

[1438] Example prompt:

[1439] "I work well in teams and often demonstrate leadership skills. I am also a good problem solver and enjoy tackling complex challenges."

[1440] Based on this prompt, the server collects data, pre-processes it, extracts features, analyzes strengths, and generates and distributes reports, allowing users to objectively evaluate their strengths and receive specific suggestions for action based on the results.

[1441] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1442] Step 1: Data collection

[1443] The user inputs self-evaluation and behavior records from the terminal. For example, the user inputs a prompt sentence such as "I am good at working in a team and often demonstrate leadership." The terminal sends this input data to the server. The input data is in text format, and the server receives it.

[1444] Step 2: Data Preprocessing

[1445] The server preprocesses the received text data. Specifically, it removes HTML tags and special characters to make the text clean. For example, I am good at working in a team and often demonstrate leadership skills. " HTML tags are removed from the data. The preprocessed text data is output.

[1446] Step 3: Feature Extraction

[1447] The server extracts features from the preprocessed text data. It uses natural language processing tools (e.g., NLTK and spaCy) to extract keywords and perform sentiment analysis. For example, it extracts keywords such as "teamwork," "leadership," and "problem-solving ability." The extracted feature data is output.

[1448] Step 4: Strengths analysis

[1449] The server analyzes the strengths of individuals based on the extracted feature data. Using a machine learning model (e.g., scikit-learn or TensorFlow), it compares the data with past data and calculates a score. For example, to determine that "leadership is a strength," the feature data is input into the model and a score is calculated. The analysis results are then output.

[1450] Step 5: Generate reports

[1451] The server generates a report based on the analysis results. It creates a text report with the content such as "Your strengths are leadership and problem-solving ability." The generated report is output.

[1452] Step 6: Report distribution

[1453] The server sends the generated report to the user's terminal. The user can check the report on the terminal. For example, the user can receive a report such as "Your strengths are leadership and problem-solving ability" and can objectively understand his or her strengths.

[1454] (Application example 1)

[1455] Next, a description will be given of Application Example 1 of Form Example 1. In the following description, the data processing device 12 will be referred to as a "server", and the headset type terminal 314 will be referred to as a "terminal".

[1456] In conventional factories, it was difficult to assign workers to tasks that fully utilize their strengths, making it difficult to achieve efficient work allocation. In addition, there was a lack of means to objectively evaluate the behavioral tendencies and thought patterns of each worker and to assign them optimal tasks based on that. This led to problems of reduced work efficiency and reduced motivation among workers.

[1457] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1458] In this invention, the server includes a means for objectively judging the strengths of individuals, a means for inputting the judgment result into a natural language processing tool, a means for the natural language processing tool to output a specific action proposal based on the judgment result, and a means for allocating workers to optimal tasks based on the action proposal, thereby enabling efficient task allocation that makes the most of the strengths of workers.

[1459] "Individual strengths" are the specific abilities and characteristics that each worker possesses, and are factors that contribute to work efficiency and results.

[1460] "Means of objective judgment" are methods or tools for collecting data on an individual's behavioral tendencies and thought patterns and evaluating them without subjectivity.

[1461] A "natural language processing tool" is software or algorithms that analyze text data and understand its meaning and intent.

[1462] "Judgment results" are the data or information obtained after an objective evaluation of an individual's strengths.

[1463] The "specific action suggestions" are specific actions or work contents that are recommended to the worker based on the judgment results.

[1464] A "means for allocating workers to optimal tasks" is a method or system for allocating workers to the most suitable tasks or roles, taking into account their strengths and characteristics.

[1465] The system for carrying out the present invention is for objectively determining the strengths of individuals and allocating workers to the most suitable tasks based on the results. A specific embodiment of this system will be described below.

[1466] System Configuration

[1467] The system consists of the following main components:

[1468] 1. A means to objectively assess an individual's strengths: This is software that collects and analyzes data on the behavioral tendencies and thought patterns of workers. Specifically, it uses sensors and log data to record and analyze the actions of workers.

[1469] 2. Natural Language Processing Tools: These tools are used to analyze the collected data and identify individual strengths. They use Python’s NLTK library and scikit-learn to analyze text data.

[1470] 3. Means for outputting specific action suggestions: Based on the judgment results obtained by the natural language processing tool, specific action suggestions are generated for the worker. Using the generative AI model, a prompt sentence is input and the optimal action suggestion is generated.

[1471] 4. Means for allocating workers to optimal tasks: This is an algorithm for allocating workers to optimal tasks based on action suggestions. Using KMeans clustering, we classify workers into appropriate groups and allocate tasks optimally.

[1472] Program processing explanation

[1473] The server first collects data on the behavior of workers. This is done using sensor and log data. The collected data is then analyzed using natural language processing tools. Specifically, the NLTK library is used to tokenize the text data and perform TF-IDF vectorization. After that, the workers are classified into clusters using scikit-learn's KMeans clustering.

[1474] Next, a generative AI model is used to generate specific action suggestions based on the clustering results. A prompt is input, and the generative AI model outputs optimal action suggestions. Based on these action suggestions, workers are assigned to optimal tasks.

[1475] Examples

[1476] For example, let's say you have the following worker data:

[1477] Analyze the behavioral trends of workers and propose optimal work placement. Below is the worker data.

[1478] [

[1479] {"name": "A", "behavior": "Works quickly. Good problem-solving skills."},

[1480] {"name": "B", "behavior": "Good at detailed work. Works carefully."},

[1481] {"name": "C", "behavior": "Emphasis on teamwork. Excellent communication skills."}

[1482] ]

[1483] Based on this data, the system identifies the strengths of each worker and suggests optimal task allocations. For example, Worker A, who works quickly, can be assigned to tasks that require emergency response. Worker B, who excels at detailed work, can be assigned to precision work. Worker C, who values ​​teamwork, can be assigned as a team leader.

[1484] In this way, the system makes the most of workers' strengths and achieves efficient work allocation.

[1485] The flow of the specific process in the application example 1 will be described with reference to FIG.

[1486] Step 1:

[1487] The server collects the worker's behavior data. Specifically, it records the worker's behavior using sensors and log data. The inputs include the worker's behavior log and sensor data. These data are stored in a database for subsequent analysis. The output is the collected behavior data.

[1488] Step 2:

[1489] The server preprocesses the collected behavioral data. Specifically, it uses a natural language processing tool (NLTK library) to tokenize the text data, remove non-alphabetical characters, and remove stop words. The input is the behavioral data collected in step 1. The output is the preprocessed text data.

[1490] Step 3:

[1491] The server converts the preprocessed text data into a TF-IDF vector. Specifically, it uses scikit-learn's TfidfVectorizer to convert the text data into a numerical vector. The input is the text data preprocessed in step 2. The output is a TF-IDF vector.

[1492] Step 4:

[1493] The server performs clustering using the TF-IDF vectors. Specifically, it uses scikit-learn's KMeans clustering algorithm to classify workers into multiple clusters. The input is the TF-IDF vector obtained in step 3. The output is the cluster information for each worker.

[1494] Step 5:

[1495] The server generates specific action suggestions based on the clustering results. Specifically, the generative AI model is used to input a prompt sentence and generate optimal action suggestions. The input is the cluster information and the prompt sentence. The output is the generated action suggestions.

[1496] Step 6:

[1497] The server assigns workers to optimal tasks based on the generated action proposals. Specifically, it analyzes the action proposals and executes an algorithm to assign optimal tasks to each worker. The input is the action proposals generated in step 5. The output is optimal task assignment information.

[1498] Step 7:

[1499] The server notifies the workers of the optimal work allocation information. Specifically, it uses a notification system to notify each worker of the new work allocation. The input is the optimal work allocation information obtained in step 6. The output is the notification to the workers.

[1500] Example 2

[1501] Next, a second embodiment of the second form will be described. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal".

[1502] Although conventional systems can objectively judge an individual's strengths, it is difficult to generate suggestions for linking those strengths to concrete actions. In addition, it is not clear how the generated action suggestions can be used for individual self-improvement and management, so the actual effect is limited.

[1503] The identification process by the identification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes a means for objectively judging the strengths of an individual, a means for loading the judgment result into a natural language processing tool, a means for the natural language processing tool to generate a specific action proposal based on the judgment result, and a means for outputting the action proposal. This makes it possible to automatically generate a specific action proposal for making the most of an individual's strengths, and to effectively utilize the action proposal for the individual's self-improvement and management.

[1504] "Individual strengths" refer to the specific abilities or characteristics that an individual possesses, in which they excel compared to others.

[1505] "Judgment objectively" means making an evaluation based on data and facts, without being influenced by subjectivity or emotion.

[1506] A "natural language processing tool" refers to software and algorithms for analyzing text data and understanding its meaning and structure.

[1507] "Judgment results" refer to the results of an objective evaluation of an individual's strengths.

[1508] "Action suggestions" refer to specific actions that individuals can take to make the most of their strengths.

[1509] "Outputting" refers to providing the generated information in a form usable by a user.

[1510] "Self-improvement" refers to the efforts and activities that an individual undertakes to improve his or her own abilities and knowledge.

[1511] "Management" refers to the operation and management of an organization or project.

[1512] The present invention is a system for objectively determining the strengths of an individual and generating specific action proposals based on the results of the determination. A specific embodiment of this system will be described below.

[1513] The server first collects data to objectively determine an individual's strengths. This data is obtained from various sources, such as survey results and performance evaluations. The server then analyzes this data to identify the individual's strengths.

[1514] The server then feeds the results of the identified strengths into a natural language processing tool. Specifically, the server uses spaCy, a Python natural language processing library, which is used to tokenize the text data and extract key keywords and phrases.

[1515] The server uses natural language processing tools to analyze the results of the judgment and generates specific action suggestions based on the results. For example, if the report states that "this individual has excellent team leadership," the server generates action suggestions such as "serve as a leader for team projects" and "regularly communicate with team members."

[1516] The generated action proposal is provided to the user by the server. Specifically, the action proposal is output in text format and can be viewed by the user. This allows the user to take specific actions to make the most of their strengths.

[1517] As a concrete example, here is a prompt that a user can enter into a generative AI model:

[1518] "Please suggest what action individuals should take based on this report."

[1519] Examples of specific prompts include the following:

[1520] The report states:

[1521] Strengths: Team Leadership

[1522] Details: This individual has excellent team building skills and excels at project management.

[1523] Action suggestion:

[1524] Lead a team project

[1525] Communicate with team members regularly

[1526] Regularly review project progress

[1527] In this way, the server analyzes the contents of the report and generates and outputs specific action proposals for individuals to make the most of their strengths, which can be effectively used for self-improvement and management of individuals.

[1528] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1529] Step 1: Load the report

[1530] The server reads the report output from the strengths assessment tool. Specifically, the server specifies the file path where the report is saved, opens the file, and obtains the contents. The file path of the report is required as input, and the contents of the report are obtained in text format as output.

[1531] Step 2: Analyze the report

[1532] The server analyzes the report content using natural language processing tools. Specifically, the server uses spaCy, a Python natural language processing library, to tokenize the report text and extract important keywords and phrases. The input is the report text, and the output is the extracted keywords and phrases.

[1533] Step 3: Generate action suggestions

[1534] The server generates specific action suggestions based on the analysis results. Specifically, the server suggests actions that individuals can take to make the most of their strengths based on the extracted keywords and phrases. For example, if the keyword "team leadership" is extracted, the server generates action suggestions such as "serve as a leader in a team project." The input requires the extracted keywords and phrases, and the output is a specific action suggestion.

[1535] Step 4: Output action suggestions

[1536] The server provides the generated action proposal to the user. Specifically, the server outputs the action proposal in a text format so that the user can view it. The generated action proposal is required as an input, and the action proposal in a format viewable by the user is obtained as an output.

[1537] In this way, the server analyzes the contents of the report and generates and outputs specific action proposals for individuals to make the most of their strengths, which can be effectively used for self-improvement and management of individuals.

[1538] (Application example 2)

[1539] Next, a description will be given of Application Example 2 of Form Example 2. In the following description, the data processing device 12 will be referred to as a "server", and the headset type terminal 314 will be referred to as a "terminal".

[1540] Conventional factory robot systems have difficulty automatically generating specific action suggestions to maximize production efficiency. In addition, there was no system that could objectively determine an individual's strengths and output specific action suggestions based on them. As a result, it was not possible to effectively support the improvement of production efficiency or the self-improvement of individuals.

[1541] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1542] In this invention, the server includes a means for objectively judging the strengths of individuals, a means for loading the judgment result into a natural language processing tool, a means for the natural language processing tool to output a specific action proposal based on the judgment result, a means for analyzing a production report in the factory with the natural language processing tool, and a means for proposing what action each robot should take to maximize production efficiency. This makes it possible to effectively support the improvement of production efficiency and the self-improvement of individuals.

[1543] "Individual strengths" refer to the specific abilities or characteristics that an individual possesses, in which they excel compared to others.

[1544] "Judgment objectively" means making an evaluation based on facts and data, without being influenced by subjectivity or emotion.

[1545] "Natural language processing tools" refer to technology and software that allows computers to analyze and understand human language.

[1546] An "action proposal" is a proposal that outlines specific actions or steps to be taken to achieve a particular goal.

[1547] An "in-factory production report" refers to a document that records the status and results of production activities in a factory.

[1548] "Analyze" refers to examining data or information in detail to clarify its structure and meaning.

[1549] "Production efficiency" refers to the ratio of production results obtained to the resources input, and is an indicator of efficient production activities.

[1550] A "robot" refers to a mechanical device that performs work automatically, especially those used in production activities in factories and other places.

[1551] To "propose" means to present a solution or plan of action for a particular problem or challenge.

[1552] A system for carrying out the present invention has the following configuration: A server includes means for objectively judging the strengths of individuals, means for loading the judgment results into a natural language processing tool, means for the natural language processing tool to output specific action suggestions based on the judgment results, means for analyzing production reports within the factory with the natural language processing tool, and means for proposing what actions each robot should take to maximize production efficiency.

[1553] Program processing explanation

[1554] The server first collects data to objectively judge an individual's strengths. This data includes the individual's past performance, evaluations, skill sets, etc. Next, the collected data is loaded into a natural language processing tool to analyze the individual's strengths. For this analysis, a Japanese natural language processing model is loaded using the spacy library, and a summary is generated using the transformers library pipeline.

[1555] Based on the analysis, natural language processing tools suggest how individuals can take action to make the most of their strengths, using generative AI models to generate specific action suggestions.

[1556] In addition, the system uses natural language processing tools to analyze production reports from within the factory and proposes what actions each robot should take to maximize production efficiency. This analysis involves examining the contents of the reports in detail and processing and calculating data to clarify their structure and meaning.

[1557] Examples

[1558] As a concrete example, we use a report on production efficiency within a factory as input. Below is an example of a prompt sentence to be input to the generative AI model.

[1559] This is a report on production efficiency in a factory. In the current production line, a bottleneck occurs in a specific process. In order to eliminate this bottleneck, it is necessary to optimize the operation of the robots. Specifically, production efficiency can be improved by adjusting the timing of material supply and the operating speed of each robot.

[1560] Taking this prompt as input, the server generates the following action suggestions:

[1561] Adjust the timing of material supply.

[1562] Adjust the movement speed of each robot.

[1563] This makes it possible to provide specific action suggestions for factory robots to maximize production efficiency.

[1564] The flow of the specific process in the application example 2 will be described with reference to FIG.

[1565] Step 1:

[1566] The server collects data to objectively determine an individual's strengths.

[1567] Inputs: Data such as an individual’s past performance, ratings, and skill sets.

[1568] Output: The collected data.

[1569] Specific operation: The server retrieves data on individual performance and evaluations from databases and external systems and stores this in an internal database.

[1570] Step 2:

[1571] The server loads the collected data into a natural language processing tool to analyze each individual's strengths.

[1572] Input: Collected data.

[1573] Output: Analysis of individual strengths.

[1574] How it works: The server loads a Japanese natural language processing model using the spacy library and analyzes the collected data. The analysis results are output as text data showing the individual's strengths.

[1575] Step 3:

[1576] The server generates specific action suggestions based on the analysis results.

[1577] Input: Personal strengths analysis results.

[1578] Output: Specific suggestions for action.

[1579] Specific Actions: The server uses a generative AI model to generate action suggestions that show an individual what actions to take to best utilize their strengths.

[1580] Step 4:

[1581] The server analyzes production reports from within the factory using natural language processing tools.

[1582] Input: In-factory production report.

[1583] Output: Analysis results of production report.

[1584] Specific operation: The server uses the transformers library pipeline to generate a summary of the production report and perform detailed analysis of the report contents.

[1585] Step 5:

[1586] Based on the analysis results, the server suggests what actions each robot should take to maximize production efficiency.

[1587] Input: Analysis results of production report.

[1588] Output: Specific suggestions for action.

[1589] Specific actions: The server uses the generative AI model to generate specific action suggestions to improve production efficiency, for example, making suggestions on adjusting the timing of material supply or the speed of robot movements.

[1590] Step 6:

[1591] The server provides the generated action suggestions to the user.

[1592] Input: Specific proposals for action.

[1593] Output: Action suggestions provided to the user.

[1594] Specific operation: The server sends the generated action proposal to the user's terminal so that the user can review it.

[1595] Example 3

[1596] Next, a third embodiment of the third embodiment will be described. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal".

[1597] In conventional personnel allocation systems, it was difficult to fully utilize the strengths of individuals, and personnel were often not assigned to appropriate tasks. In addition, there was a lack of means to objectively judge individuals' strengths and generate specific action proposals based on them, making it difficult for management to make effective personnel allocations.

[1598] The identification process by the identification processing unit 290 of the data processing device 12 in the third embodiment is realized by the following means. In this invention, the server includes a means for objectively judging the strengths of individuals, a means for loading the judgment result into a natural language processing tool, a means for the natural language processing tool to input a prompt sentence into a generative AI model based on the judgment result and output a specific action proposal, and a means for providing the action proposal to management. This enables personnel allocation that makes the most of individual strengths.

[1599] "Individual strengths" are specific abilities or characteristics that an individual possesses, and are the factors that enable them to perform better than others in a task or activity.

[1600] "Means of objective judgment" are methods or tools for accurately evaluating an individual's strengths based on data and evaluation criteria, without relying on subjectivity.

[1601] A "natural language processing tool" is software or algorithms for analyzing text data and understanding its meaning.

[1602] A "generative AI model" is an artificial intelligence model that generates new information or suggestions based on input data.

[1603] A "prompt" is an instruction or question input to a generative AI model that triggers the model to generate an appropriate output.

[1604] "Action suggestions" are suggestions that provide specific actions or work instructions based on an individual's strengths and analysis results.

[1605] "Management" refers to the people or departments responsible for running and managing an organization or team.

[1606] The present invention is a system for objectively determining the strengths of an individual and generating specific action proposals based on the results. A specific embodiment of this system is described below.

[1607] Hardware and Software Used

[1608] Hardware: Servers, terminals (PCs and smartphones)

[1609] Software: Generative AI models (e.g. GPT-4), natural language processing tools (e.g. SpaCy)

[1610] System Overview

[1611] The system starts with the user accessing the strengths assessment tool using a terminal and inputting information on self-evaluation and work performance. The server receives the data sent by the user and analyzes it using natural language processing tools. Based on the analysis results, it inputs prompt sentences into the generative AI model to generate specific action suggestions. Finally, the server provides the generated action suggestions to management.

[1612] Examples

[1613] 1. The user accesses the strengths assessment tool and enters information

[1614] The user uses the terminal to access the web page or application of the strengths assessment tool, answers questions about self-evaluation and work performance, and inputs the required information.

[1615] Example: A user answers "Strategic planning" to the question "What do you do best?"

[1616] 2. The server receives and analyzes the user input data

[1617] The server receives the data sent by the user and analyzes it using a natural language processing tool (e.g. SpaCy). As a result of the analysis, the user's strengths are identified.

[1618] Example: The server parses the answer "strategic planning" and identifies the user's strength as "strategic thinking."

[1619] 3. The server inputs a prompt sentence into the generative AI model based on the analysis results and generates action suggestions.

[1620] Based on the analysis results, the server inputs a prompt sentence into a generative AI model (e.g., GPT-4), which then generates a specific action suggestion based on the prompt sentence.

[1621] Example: The server inputs the prompt sentence "This individual's strength is strategic thinking. Please suggest what kind of work this individual should be involved in to utilize this strength" to the generative AI model, and the generative AI model generates an action suggestion such as "Suggest involving this individual in strategic planning and business planning."

[1622] 4. The server provides the generated action proposals to the management.

[1623] The server provides the generated action proposals to management, who then receives the proposals and assigns personnel to maximize the use of each individual's strengths.

[1624] Example: The server sends an action proposal to management, such as "I suggest that this individual be involved in strategic planning and business planning," and management assigns the relevant individual to the appropriate task based on that proposal.

[1625] In this way, the system supports personnel allocation that makes the most of each individual's strengths. The flow of the identification process in the third embodiment will be described with reference to FIG.

[1626] Step 1:

[1627] The user accesses the strengths assessment tool and inputs information.

[1628] Specific actions: The user uses the terminal to access the strengths assessment tool web page or application. The user answers questions about self-evaluation and work performance and enters the required information.

[1629] Input: Information about the user's self-assessment and job performance.

[1630] Output: The user's input data.

[1631] Step 2:

[1632] The server receives and analyzes the user's input data.

[1633] Specific operation: The server receives the data sent by the user and analyzes the data using a natural language processing tool (e.g. SpaCy). As a result of the analysis, the user's strengths are identified.

[1634] Input: Data entered by the user.

[1635] Output: Analysis results identifying user strengths.

[1636] Step 3:

[1637] Based on the analysis results, the server inputs prompt sentences into the generative AI model and generates action suggestions.

[1638] Specific action: Based on the analysis results, the server inputs a prompt sentence into the generative AI model (e.g. GPT-4). The generative AI model generates specific action suggestions based on the prompt sentence.

[1639] Input: Analysis result and prompt.

[1640] Output: Specific action suggestions from the generative AI model.

[1641] Step 4:

[1642] The server provides the generated action suggestions to the management.

[1643] Specific operation: The server provides the generated action proposals to management. Management receives the proposals and assigns personnel to make the most of each individual's strengths.

[1644] Input: Generated action suggestions.

[1645] Output: Action suggestions provided to management.

[1646] (Application example 3)

[1647] Next, a description will be given of Application Example 3 of Form Example 3. In the following description, the data processing device 12 will be referred to as a "server", and the headset type terminal 314 will be referred to as a "terminal".

[1648] In conventional personnel allocation systems, the strengths of each worker could not be fully utilized, and optimal work allocation was often not performed. As a result, there were problems with reduced work efficiency and lack of improvement in productivity. In addition, there was a lack of means to objectively judge the strengths of workers and propose specific actions based on that, making it difficult for management to perform appropriate personnel allocation.

[1649] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 3 is realized by the following means.

[1650] In this invention, the server includes a means for objectively judging the strengths of individuals, a means for inputting the judgment result into a natural language processing tool, a means for the natural language processing tool to output a specific action proposal based on the judgment result, and a means for proposing an optimal task allocation for workers based on the action proposal, thereby enabling optimal task allocation that makes the most of the strengths of each worker.

[1651] "Individual strengths" refers to the unique abilities, skills, and areas of expertise that a particular individual possesses.

[1652] "Means of objective judgment" refers to a method of accurately evaluating an individual's strengths based on data and evaluation criteria, without relying on subjectivity.

[1653] "Natural language processing tools" refers to computer programs and algorithms that understand, analyze, and generate human language.

[1654] "Judgment results" refers to data and information obtained as a result of an objective evaluation of an individual's strengths.

[1655] "Specific action suggestions" refer to suggestions that specifically indicate what actions an individual should take based on the judgment results.

[1656] "Optimal worker allocation" refers to the allocation of workers to perform tasks most efficiently and effectively based on their strengths and capabilities.

[1657] A "server" refers to a computer system that processes and stores data on a network.

[1658] The system for carrying out the present invention objectively judges the strengths of individuals and proposes optimal work allocation based on the results. A specific embodiment of this system will be described below.

[1659] The server first collects data to objectively determine an individual's strengths. This data can come from a worker's past performance, skill assessments, feedback, etc. The server then loads this data into a natural language processing tool that uses OpenAI's API and includes a generative AI model to analyze individual strengths.

[1660] The natural language processing tool analyzes the collected data and identifies the strengths of the individual. For example, if a worker is good at precision work, "precision work" is identified as the worker's strength. The result of this judgment is sent to the server.

[1661] Next, the server generates specific action suggestions based on the results of this judgment. For example, a suggestion is generated to assign a worker who is good at precision work to the assembly of precision equipment. This action suggestion is used to determine the optimal task allocation of workers.

[1662] As a concrete example, by inputting the following prompt sentences into a generative AI model, we can obtain optimal work placement suggestions:

[1663] Worker strengths data:

[1664] Person A: Precision work

[1665] Person B: Physical strength

[1666] Person C: Strategic thinking

[1667] Work content and required strengths:

[1668] Precision equipment assembly: precision work

[1669] Lifting heavy objects: Physical strength

[1670] Production Line Optimization: Strategic Thinking

[1671] Based on the above data, please suggest the optimal work arrangement.

[1672] By inputting this prompt into a generative AI model, the server can obtain optimal work placement suggestions, resulting in efficient work placement that makes the most of the strengths of each worker.

[1673] The hardware used is a computer system that processes and stores data over a network, and the software uses Python and OpenAI APIs, which makes it possible to analyze the strengths of each worker and propose optimal work placement.

[1674] The flow of the specific process in the application example 3 will be described with reference to FIG.

[1675] Step 1:

[1676] The server collects data to objectively judge the strengths of workers. As input, it receives data such as the worker's past performance, skill evaluation, and feedback, and stores it in a database. As output, it obtains the collected data.

[1677] Step 2:

[1678] The server loads the collected data into a natural language processing tool. As input, it uses the data collected in step 1 and sends the data to the natural language processing tool. As output, it gets the data in a format that the natural language processing tool can parse.

[1679] Step 3:

[1680] The natural language processing tool analyzes the input data and identifies the strengths of the workers. As input, it uses the data obtained in step 2 and performs analysis using a generative AI model. As output, data is obtained in which the strengths of each worker are identified.

[1681] Step 4:

[1682] The server generates specific action suggestions based on the strengths data obtained from the natural language processing tool. As input, it uses the strengths data obtained in step 3 and inputs prompt sentences into the generative AI model. As output, it obtains specific action suggestions for each worker.

[1683] Step 5:

[1684] The server proposes an optimal task placement for workers based on the generated action proposals. As input, it uses the action proposals obtained in step 4 and matches the tasks with the required strengths. As output, it obtains an optimal task placement proposal.

[1685] Step 6:

[1686] The server notifies the workers and management of the optimal work placement proposal. As input, it uses the work placement proposal obtained in step 5 and sends information to the workers and management via the notification system. As output, the workers and management receive the optimal work placement proposal.

[1687] In addition, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1688] "Example 1"

[1689] In one embodiment of the present invention, a strengths assessment tool such as Gallup's StrengthsFinder is used as a means for objectively assessing an individual's strengths. This tool analyzes an individual's behavioral tendencies and thought patterns, and outputs the results as a report. Next, a natural language processing tool reads this report. This tool analyzes the contents of the report and generates specific action suggestions based on the results. Furthermore, an emotion engine recognizes the user's emotions and generates specific action suggestions based on the emotions. Specifically, if the user is feeling joy, an action that will increase the joy is suggested. Also, if the user is feeling sad, an action that will reduce the sadness is suggested.

[1690] "Example 2"

[1691] In another embodiment of the present invention, the emotion engine generates specific action suggestions based on the user's emotions to support personal self-improvement, such as when the user is excited, action suggestions are made to leverage the excitement to learn new skills, and when the user is depressed, action suggestions are made to overcome depression.

[1692] "Example 3"

[1693] In yet another embodiment of the present invention, the emotion engine generates specific action suggestions to utilize the user's emotions for emotion management, for example, if the user is feeling happy, it suggests an action to share the happiness, and if the user is feeling angry, it suggests a dialogue or discussion to resolve the anger.

[1694] The process flow of each embodiment will be described below.

[1695] "Example 1"

[1696] Step 1: Users assess their own strengths using a strengths-determining tool such as Gallup's StrengthsFinder.

[1697] Step 2: The strengths assessment tool analyzes the user's behavioral tendencies and thought patterns and outputs the results in a report.

[1698] Step 3: A natural language processing tool reads the report and analyzes its content.

[1699] Step 4: Natural language processing tools generate specific action suggestions based on the analysis results.

[1700] Step 5: The emotion engine recognizes the user's emotion.

[1701] Step 6: The emotion engine generates specific action suggestions based on the emotions it recognizes.

[1702] "Example 2"

[1703] Step 1: The emotion engine recognizes the user's emotion.

[1704] Step 2: Based on the emotions recognized by the emotion engine, specific action suggestions are generated to support the individual's self-improvement.

[1705] "Example 3"

[1706] Step 1: The emotion engine recognizes the user's emotion.

[1707] Step 2: Based on the emotions recognized by the emotion engine, specific action suggestions are generated for use in management.

[1708] Example 1

[1709] Next, a description will be given of Example 1 of the embodiment 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal".

[1710] Conventional systems for assessing individual strengths lacked specific action suggestions that utilize the results of the strength assessment, which meant that users could not effectively utilize the results in self-improvement and management. In addition, the system did not take into account the user's emotions when proposing actions, which meant that appropriate support was not provided according to the user's emotional state.

[1711] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1712] In this invention, the server includes a means for objectively judging an individual's strengths, a means for loading the judgment result into a natural language processing tool, a means for the natural language processing tool to output a specific action proposal based on the judgment result, a means for recognizing the user's emotion using an emotion recognition engine, and a means for generating an action proposal according to the emotion based on the result of the emotion recognition engine. This makes it possible to propose a specific action that makes use of the user's strengths, and further to provide appropriate support according to the user's emotional state.

[1713] "Means for objectively assessing individual strengths" refers to tools or algorithms that analyze an individual's behavioral tendencies and thought patterns and identify their strengths based on the results.

[1714] A "natural language processing tool" is software or algorithms used to analyze text data and understand and process its content.

[1715] An "emotion recognition engine" is software or algorithms used to analyze a user's emotional state and identify those emotions.

[1716] The "means for outputting action suggestions" refers to a function or algorithm for suggesting specific actions to the user based on the analysis results.

[1717] A "means for generating action suggestions according to emotions" is a function or algorithm for taking into account the emotional state of the user and suggesting actions appropriate to those emotions.

[1718] This invention is a system that objectively judges the strengths of individuals and proposes specific actions based on the results. This system works in cooperation with a server, a terminal, and a user.

[1719] First, the user uses a terminal to input information about his / her own behavioral tendencies and thought patterns. This information is collected through questionnaires or self-evaluation sheets. The terminal then transmits the user's response data to a server.

[1720] The server uses the received user data to objectively determine the strengths of the individual. Specifically, it uses a strengths assessment tool such as Gallup's StrengthsFinder tool. The server inputs the user data into this tool and analyzes the individual's behavioral tendencies and thought patterns. The analysis results are generated as a report and saved in text format.

[1721] Next, the server passes the generated report to a natural language processing tool (e.g., Google Cloud Natural Language API) to analyze the content. The natural language processing tool analyzes the text data of the report and returns the results to the server. Based on the analysis results, the server generates specific action suggestions that utilize the user's strengths. For example, if the user's strength is "leadership," it will make specific action suggestions to demonstrate leadership.

[1722] Furthermore, the server recognizes the user's emotions using an emotion recognition engine (e.g., IBM Watson Tone Analyzer). The user's emotion data is obtained from input from the terminal and past behavioral history. The emotion recognition engine analyzes the user's emotional state and returns the results to the server. Based on the emotion analysis results, the server generates specific action suggestions according to the user's emotions. For example, if the user is feeling happy, the server suggests actions that will increase that happiness. Also, if the user is feeling sad, the server suggests actions that will reduce that sadness.

[1723] As a concrete example, let us consider a case where the user is determined to have strengths in "leadership" and "empathy." The server generates the following action suggestions:

[1724] Demonstrate leadership by taking the lead in setting goals for your team.

[1725] Use your empathy and actively listen to your team members' opinions.

[1726] If the emotion engine recognizes the user's emotions and determines that the user is feeling happy, it will suggest the following actions:

[1727] Share success stories with your team to amplify the joy.

[1728] If the user is feeling sad, the following action suggestions are made:

[1729] To ease your grief, set aside time to talk with a trusted colleague.

[1730] Example prompt:

[1731] Analyze user strengths and generate specific action suggestions based on user behavioral tendencies and thought patterns. Consider user emotions and suggest actions to increase joy or reduce sadness.

[1732] In this way, a system is realized in which the server, terminal, and user work together to objectively judge an individual's strengths and provide specific suggestions for action.

[1733] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1734] Step 1:

[1735] The user uses the terminal to input information about his / her own behavioral tendencies and thought patterns. The input information is collected through questionnaires or self-evaluation sheets. The terminal transmits the user's response data to the server.

[1736] Input: Information about the user's behavioral tendencies and thought patterns

[1737] Output: User data sent to the server.

[1738] Specific operation: The user answers questions displayed on the device screen, and the device sends the data to the server.

[1739] Step 2:

[1740] The server uses the received user data to objectively judge the strengths of the individual. Specifically, it uses a strengths judgment tool. The server inputs the user data into this tool and analyzes the individual's behavioral tendencies and thought patterns.

[1741] Input: User data

[1742] Output: Analysis results from the strengths assessment tool

[1743] Specific operation: The server calls the API of the strengths assessment tool, sends user data, and receives the analysis results.

[1744] Step 3:

[1745] The server generates a report summarizing the user's strengths based on the analysis results obtained from the strengths assessment tool, and saves the report in text format.

[1746] Input: Analysis results of strengths assessment tool

[1747] Output: Text report

[1748] Specific operation: The server converts the analysis results into a text report and stores it in a database.

[1749] Step 4:

[1750] The server passes the generated report to a natural language processing tool for content analysis. The natural language processing tool analyzes the text data of the report and returns the results to the server.

[1751] Input: Text report

[1752] Output: Analysis results from natural language processing tools

[1753] Specific operation: The server sends the report's text data to a natural language processing tool and receives the analysis results.

[1754] Step 5:

[1755] The server generates specific action suggestions that utilize the user's strengths based on the analysis results obtained from the natural language processing tool.

[1756] Input: Analysis results of natural language processing tools

[1757] Output: Specific action suggestions

[1758] Specific operation: The server runs an algorithm to generate action suggestions based on the analysis results, and generates the action suggestions in text format.

[1759] Step 6:

[1760] The server uses an emotion recognition engine to recognize the user's emotions. The user's emotion data is obtained from input from the terminal and from the user's past behavior history.

[1761] Input: User emotion data

[1762] Output: Emotion analysis results by the emotion recognition engine

[1763] Specific operation: The user inputs his / her current emotion through the terminal, and the server sends the emotion data to the emotion recognition engine and receives the analysis results.

[1764] Step 7:

[1765] The server generates specific action suggestions according to the user's emotions based on the emotion analysis results obtained from the emotion recognition engine.

[1766] Input: Emotion analysis results from the emotion recognition engine

[1767] Output: Specific action suggestions based on emotions

[1768] Specific operation: The server runs an algorithm that generates action suggestions based on the results of emotion analysis. If the user is feeling happy, the server suggests actions that will increase that joy, and if the user is feeling sad, the server suggests actions that will reduce that sadness.

[1769] (Application example 1)

[1770] Next, a description will be given of Application Example 1 of Form Example 1. In the following description, the data processing device 12 will be referred to as a "server", and the headset type terminal 314 will be referred to as a "terminal".

[1771] Conventional tools for determining individual strengths identify strengths by analyzing an individual's behavioral tendencies and thought patterns, but it is difficult to link the results to specific action suggestions. In addition, since action suggestions do not take into account the user's emotional state, there is a problem in that appropriate suggestions cannot be made according to the user's current emotions. Furthermore, there is a lack of concrete measures to personalize shopping experiences in physical stores.

[1772] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1773] In this invention, the server includes a means for objectively judging an individual's strengths, a means for loading the judgment result into a natural language processing tool, a means for the natural language processing tool to output a specific action proposal based on the judgment result, a means for recognizing a user's emotion, a means for generating an action proposal based on the emotion, and a means for proposing optimal products and services based on the user's strengths and emotional state. This makes it possible to propose specific actions according to the user's strengths and emotional state, thereby personalizing the shopping experience at a brick-and-mortar store.

[1774] "Means of objectively assessing an individual's strengths" refers to a method for analyzing an individual's behavioral tendencies and thought patterns and identifying that individual's strengths based on the results.

[1775] The "means for reading the judgment result into a natural language processing tool" refers to a means for inputting the result of judging an individual's strengths into a natural language processing tool.

[1776] "The means by which the natural language processing tool outputs specific action suggestions based on the judgment results" refers to the means by which the natural language processing tool analyzes the judgment results of an individ...

Claims

1. A means of objectively assessing individual strengths, a means for reading the result of the determination by the determining means into a natural language processing tool; A means for outputting a specific action proposal based on the judgment result by the natural language processing tool; A means for collecting data input from a user; A means for pre-processing the data collected by the collecting means; means for extracting features from the data preprocessed by the preprocessing means; A means for analyzing strengths of the user based on the features extracted by the means for extracting features; A means for generating a report based on the analysis result by the analyzing means; means for delivering the report generated by said generating means to a user; A system including:

2. The system according to claim 1 , wherein the natural language processing tool outputs specific action suggestions for supporting an individual's self-improvement based on the judgment result.

3. The system according to claim 1 , wherein the natural language processing tool outputs specific action suggestions for utilizing the judgment results in management.

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