system

Abstract

We provide the system. [Solution] Means of collecting information about the geographical areas where users gather, A means of analyzing the collected information and quantifying the evaluation of the area, A means of evaluating geographical areas and matching them with information on the infrastructure facilities of telecommunications carriers, A means of delivering promotional information to mobile devices within the relevant area, A system including a means for outputting proposals regarding the development of the area in question.

Description

Technical Field

[0001] The technology of this disclosure relates to a system.

Background Art

[0002] Patent Document 1 discloses a method for controlling a persona chatbot, which is performed by at least one processor, and includes steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to an explanation of a character of the chatbot, 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

Summary of the Invention

Problems to be Solved by the Invention

[0004] In the conventional promotion method of a communication network, it is difficult to provide an appropriate network service for an area where many users gather. As a result, there is a problem that the quality of the network experience deteriorates particularly at highly evaluated spots. Also, in an area where the communication infrastructure is insufficient despite being highly evaluated, efficient resource allocation is not made and the potential value cannot be exerted. There is a demand for solving such problems and improving and optimizing network services focusing on valuable user acquisition areas.

Means for Solving the Problems

[0005] This invention is a system that collects information on geographical areas where users gather, analyzes that information to quantify the evaluation of the area, and determines the value of the area by comparing the evaluation with the infrastructure information of the telecommunications carrier. Furthermore, it improves the service value to users by distributing promotional information to mobile devices within the relevant area. In addition, it provides a means to promote the development of communication infrastructure to maximize potential value by providing development proposals based on the area evaluation as a report to relevant departments within the company. In this way, it efficiently utilizes the value of the communication network while improving the user experience.

[0006] "User" refers to an individual or group that is eligible to receive communication network services or promotions.

[0007] A "geographic area" refers to a specific geographical location or region, and the area within which communication services are provided.

[0008] "Information" refers to data about areas where users gather, specifically including data on word-of-mouth, ratings, and movement patterns.

[0009] "Analysis" refers to data processing performed to quantify collected information data and generate evaluation scores.

[0010] "Evaluation" refers to an indicator that shows the reputation or value of an area, either numerically or qualitatively, derived from the analyzed information.

[0011] A "telecommunications carrier" refers to a company or organization that provides and manages telecommunications network infrastructure.

[0012] "Basic infrastructure information" refers to data related to network infrastructure, including information on the location of base stations and allocated frequency bands.

[0013] "Reconciliation" refers to the process of checking and comparing the relationships between different pieces of information or datasets.

[0014] "Promotional information" refers to marketing messages such as discounts and benefits offered to users within a specific area.

[0015] A "mobile device" refers to a portable electronic device that has the ability to receive information via a communication network.

[0016] "Maintenance proposals" refer to specific recommendations regarding the improvement and expansion of network infrastructure, and serve as a reference for telecommunications carriers' infrastructure strategies.

[0017] A "report" is a document that summarizes the results of an evaluation or analysis, and is created with the purpose of presenting specific proposals or conclusions. [Brief explanation of the drawing]

[0018] [Figure 1] This is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] This is a conceptual diagram showing an example of the essential functions of a data processing device and a smart device according to the first embodiment. [Figure 3] This is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] This is a conceptual diagram showing an example of the main functions of a data processing device and smart glasses according to the second embodiment. [Figure 5] This is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] This is a conceptual diagram showing an example of the main functions of a data processing device and a headset-type terminal according to the third embodiment. [Figure 7] This is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8]It is a conceptual diagram showing an example of the main functions of a data processing device and a robot according to the fourth embodiment. [Figure 9] It shows an emotion map to which a plurality of emotions are mapped. [Figure 10] It shows an emotion map to which a plurality of emotions are mapped. [Figure 11] It is a sequence diagram showing the processing flow of the data processing system in Example 1. [Figure 12] It is a sequence diagram showing the processing flow of the data processing system in Application Example 1. [Figure 13] It is a sequence diagram showing the processing flow of the data processing system in Example 2 when an emotion engine is combined. [Figure 14] It is a sequence diagram showing the processing flow of the data processing system in Application Example 2 when an emotion engine is combined.

Mode for Carrying Out the Invention

[0019] 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.

[0020] First, the language used in the following description will be explained.

[0021] In the following embodiments, the signed processor (hereinafter simply referred to as "processor") may be a single arithmetic unit or a combination of a plurality of arithmetic units. Also, the processor may be a single type of arithmetic unit or a combination of a plurality of types of arithmetic units. Examples of arithmetic units 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), and the like.

[0022] In the following embodiments, signed RAM (Random Access Memory) is a memory that temporarily stores information and is used as work memory by the processor.

[0023] In the following embodiments, the signed storage is one or more non-volatile storage devices that store various programs and various parameters. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), or magnetic tapes.

[0024] In the following embodiments, the signed communication interface (I / F) is an interface that includes a communication processor and an antenna, etc. The communication interface manages communication between multiple computers. Examples of communication standards applicable to the communication interface include wireless communication standards such as 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), or Bluetooth (registered trademark).

[0025] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." That is, "A and / or B" means that it may be A alone, or B alone, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" applies when expressing three or more things linked by "and / or."

[0026] [First Embodiment]

[0027] Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment.

[0028] As shown in Figure 1, the 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.

[0029] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0030] The smart device 14 comprises a computer 36, a reception device 38, an output device 40, a camera 42, and a communication interface 44. The computer 36 comprises a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The reception device 38, output device 40, and camera 42 are also connected to the bus 52.

[0031] The reception device 38 is equipped with a touch panel 38A and a microphone 38B, etc., and receives user input. The touch panel 38A receives user input by detecting contact with an object (e.g., a pen or finger). The microphone 38B receives user input by detecting the user's voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and 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.

[0032] 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 perceptible to the user 20 (e.g., audio 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 audio according to instructions from the processor 46. The camera 42 is a small digital camera equipped with an optical system such as a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0033] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various types of information between processor 46 and processor 28 via network 54.

[0034] Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0035] As shown in Figure 2, in the data processing device 12, a specific processing is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" related to the technology of this 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 according to the specific processing program 56 executed on the RAM 30.

[0036] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0037] In the smart device 14, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The reception output program 60 is used in conjunction with a specific processing program 56 by the data processing system 10. 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 processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0038] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0039] The embodiments for implementing the present invention will be described focusing on the server, terminal, and user. The invention utilizes a system that collects, analyzes, and verifies information regarding the geographical areas where users gather, distributes promotional information, and generates maintenance suggestions. The server operates as the core of this system.

[0040] The server first collects reviews and ratings information about an area from online data sources. This data is obtained using APIs from social media, review sites, etc., and stored in a database. For example, rating data for a particular tourist spot can be obtained from a specific rating site.

[0041] Next, the server analyzes the collected data. It analyzes the data obtained using natural language processing technology and quantifies the evaluation of specific areas based on that analysis. As a result of the analysis, it becomes possible to identify areas with high ratings, for example.

[0042] The server compares the analyzed evaluation information with the infrastructure information of the communication network. This information includes the location of base stations and frequency bands. Based on the comparison results, the server evaluates the quality of communication services in each area.

[0043] If a highly-rated area has adequate network coverage, the server will deliver promotional information to mobile devices in that area. This promotional information may include data discount coupons or advertising messages. For example, a coupon offering limited-time additional data usage might be sent to users in a specific area.

[0044] On the other hand, for areas with high ratings but insufficient network coverage, the server generates improvement proposals. This is fed back to the company's communications infrastructure department as a report showing the area's value. This feedback report includes area evaluations, analysis of user flow patterns, and potential measures to improve communications services.

[0045] In this way, we can improve the value of services for users and provide a system that efficiently utilizes communication network resources.

[0046] The following describes the processing flow.

[0047] Step 1:

[0048] The server collects information about geographical areas. Specifically, the server retrieves data from publicly available online data sources, such as social media and review sites, using APIs. This is a process of collecting relevant reviews and ratings based on specific keywords and location information.

[0049] Step 2:

[0050] The server analyzes the collected information to quantify the area's evaluation. Specifically, the server uses natural language processing algorithms to analyze the word-of-mouth text, extracting positive or negative words to generate a score. This score is used as the evaluation of that area.

[0051] Step 3:

[0052] The server compares the analyzed evaluation data with information on the infrastructure of the communication network. Specifically, it compares the quantified evaluation of each geographical area with base station and frequency data held by the telecommunications carrier. This allows it to determine whether the network coverage in areas with high evaluations is sufficient.

[0053] Step 4:

[0054] The server delivers promotional information to mobile devices in high-rated areas with sufficient coverage. Specifically, the server sends promotional content via app notifications and SMS to user devices registered in those areas. This includes, for example, coupon information for additional data usage.

[0055] Step 5:

[0056] The server generates improvement proposals for areas with insufficient coverage. Specifically, the server creates reports based on area evaluations and user flow data, and presents them to the internal infrastructure department to recommend network improvement measures for those areas. This feedback supports future base station development and frequency allocation decision-making.

[0057] (Example 1)

[0058] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0059] Traditional communication services, despite having a high reputation in areas where users congregate, sometimes fail to provide adequate network coverage. Furthermore, they struggle to effectively deliver region-specific promotional information to users. This results in a compromised user experience and makes optimizing the communication environment difficult.

[0060] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0061] In this invention, the server includes means for collecting data on areas where users gather, means for quantifying the evaluation of the area using natural language processing technology based on the collected data, and means for comparing the evaluation information of the area with network equipment data of a telecommunications company. This makes it possible to provide optimal communication services to highly-rated areas and to deliver effective promotional information to users.

[0062] "Users" refer to individual people who use information services.

[0063] "Region" refers to a specific geographical area, which is the location where communication services are evaluated.

[0064] "Data" refers to materials containing information, and in this context, it refers to user reviews and information about network equipment.

[0065] "Means of collection" refers to methods or devices used to acquire data about the areas where users gather.

[0066] "Natural language processing technology" refers to the technology that enables computers to understand and analyze human language.

[0067] "Methods for quantifying evaluation" refer to methods of expressing the appeal and quality of a region numerically using analyzed information.

[0068] "Means of matching" refers to techniques or methods for verifying the consistency or relevance between different data.

[0069] "Advertising information" refers to promotional messages about specific products or services.

[0070] A "telecommunications company" refers to a company that provides telecommunications services.

[0071] "Network equipment data" refers to information about communication infrastructure such as base stations and frequency bands.

[0072] To implement this invention, a system in which a server plays a central role is utilized. The server collects and analyzes various data and provides appropriate communication services and promotional information to the areas where users are concentrated.

[0073] First, the server collects review and rating data about a region from online data sources. APIs from social media and review sites on the internet are used for this collection. This data is stored in a database in JSON format. A specific example is obtaining the reputation of a tourist destination from a particular review site.

[0074] The server then applies natural language processing techniques to the collected data. Open-source natural language processing libraries (such as NLTK or SpaCy) are used to analyze the acquired reviews and ratings, quantifying the region's evaluation. This analysis makes it possible to identify regions with high ratings.

[0075] Next, the server compares the regional evaluation information with the infrastructure information of the communication network. This comparison uses GIS data, combining the communication carrier's base station information, frequency bands, and regional evaluations to assess the communication service quality in each area. Based on this evaluation, the server sends promotional information to the user's device. For example, it could distribute offers such as "20% extra data this weekend only" to the user's mobile device.

[0076] For areas with high ratings but insufficient network coverage, the server generates a report with improvement suggestions. This report includes the region's rating score, user behavior patterns, and improvement proposals, and is fed back to the company's communications infrastructure department. This aims to improve both the communication environment and the user experience.

[0077] As an example of a prompt for input to the generating AI model, "Create suggestions for improving communication quality based on user evaluation data in a specific region." This allows for the efficient and effective provision of services optimized for each region.

[0078] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0079] Step 1:

[0080] The server collects local review and word-of-mouth data from social media and review sites on the internet via APIs. It takes user posts and ratings as input and stores them in a database in JSON format. The output at this stage is a set of structured text data.

[0081] Step 2:

[0082] The server analyzes the collected data using a natural language processing library. The input is the word-of-mouth data collected in step 1. Specifically, the server analyzes the text and executes an algorithm that quantifies the positive and negative tendencies of the ratings. The output is the rating score for each region.

[0083] Step 3:

[0084] The server compares the analyzed evaluation scores with information on the infrastructure of the communication network. The inputs are regional evaluation scores and network equipment data such as base station information. Specifically, GIS data is used to compare this data and evaluate the communication service quality for each region. The output is a communication quality report for each area.

[0085] Step 4:

[0086] The server sends promotional information to mobile devices only if there is adequate network coverage in a highly-rated area. The input is the quality report and promotional information obtained in step 3. Specifically, the server delivers advertisements and coupons to the device using push notifications. The output is the promotional message displayed on the user's device.

[0087] Step 5:

[0088] The server generates improvement suggestion reports for areas with a high rating of insufficient network coverage. Inputs include communication quality reports and analyzed user behavior data. Specifically, it considers improvement measures and creates a report for feedback to the communication infrastructure department. The output is the improvement suggestion report.

[0089] (Application Example 1)

[0090] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0091] In cities and tourist destinations, there is a need to maximize the appeal of the region and improve user satisfaction. Furthermore, communication service providers need information to understand the communication quality of the region and provide appropriate services. However, until now, there has been a lack of means to comprehensively analyze detailed regional evaluation information and the state of communication infrastructure to provide effective information and services to users.

[0092] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0093] In this invention, the server includes means for acquiring information about areas where users gather, means for analyzing the acquired information and quantifying the evaluation of the area, and means for comparing the evaluation of the area with the basic equipment information of the communication service provider. This makes it possible to effectively transmit promotional information according to the communication coverage status based on the evaluation information of the area, and to generate improvement suggestions based on feedback from users.

[0094] "Users" refer to individuals or groups who utilize this system and are the recipients of relevant information and services within a specific geographical area.

[0095] A "region" refers to a specific geographical area, such as a tourist destination or a city, where people gather and engage in activities.

[0096] "Means of acquiring information" refers to the processes and techniques for collecting relevant information using online data sources such as social media and review sites.

[0097] "Basic equipment information" refers to data related to the infrastructure of the communication network used by communication service providers, including the location of base stations and frequency bands.

[0098] "Means of transmitting promotional information" refers to communication methods and technologies for delivering appropriate promotional information to users' mobile communication devices.

[0099] "Means for generating improvement proposals" refers to systems and methods for analyzing regional evaluation information and user feedback to automatically create improvement measures and various proposals for communication coverage.

[0100] "Evaluation information" refers to evaluations obtained by quantifying or qualitatively analyzing user opinions such as word-of-mouth and reviews regarding a specific region.

[0101] A "mobile communication device" refers to a portable communication device, such as a smartphone or tablet, that can communicate even while on the move.

[0102] The system for realizing this invention is composed of three main components: a server, a terminal, and a user. The server acquires local data online from social media and review sites. Specifically, it collects word-of-mouth and rating information via AP and stores it in a database. The acquired information is analyzed using natural language processing technology on the server (for example, Python's NLTK library). As a result, the rating of a particular region is quantified.

[0103] The server then compares the analysis results with the basic equipment information held by the communication service provider. This basic equipment information includes data on base station locations and frequency bands. This comparison allows for an evaluation of the communication quality in the area. If a suitable communication service is provided in an area with a high evaluation, the server transmits promotional information to the terminal. This promotional information includes data communication discount coupons and advertising messages. The terminal receives this information and notifies the user.

[0104] On the other hand, in areas with high ratings but insufficient communication coverage, the server generates improvement suggestions. These suggestions are sent to the communications infrastructure department as a report highlighting the area's value. This report includes the results of the area's evaluation and user flow pattern analysis, and, like a lubricant, indicates potential improvements to communications services.

[0105] For example, users in urban areas can receive map information for their area and coupons for related tourist attractions on their smartphones while traveling. They can also automatically receive discount information for shopping areas they frequently visit.

[0106] An example of a prompt sentence for a generative AI model is, "Please tell me about popular areas in a specific city and highly-rated tourist attractions associated with those areas."

[0107] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0108] Step 1:

[0109] The server retrieves local reviews and ratings from online data sources (such as APIs). This process automatically collects data from social media and review sites. Inputs include URLs and API keys, while output is raw text data. The server receives this data and stores it in a database.

[0110] Step 2:

[0111] The server analyzes the collected text data using natural language processing (NLP) techniques. Specifically, it performs text summarization and keyword extraction. The input to this process is the raw text data from step 1, and the output is quantified evaluation data. Using NLTK or other NLP libraries, sentiment analysis of the text is performed to quantify the reputation of the area.

[0112] Step 3:

[0113] The server compares the analyzed evaluation data with communication infrastructure equipment information. This process uses base station location data and frequency band data as input. The output is a communication quality evaluation for each region. The server evaluates communication coverage for each region and determines whether there are any deficiencies.

[0114] Step 4:

[0115] The server sends promotional information to terminals in areas with good communication quality. The input consists of evaluation data and promotional content obtained in step 3, while the output is coupons and messages sent to user terminals. The server generates promotional data and sends it to terminals via the distribution system.

[0116] Step 5:

[0117] The server generates a report indicating areas with insufficient communication coverage that require improvement. The input is the communication evaluation data and user behavior data from step 3, and the output is an improvement suggestion report. The server creates the report and provides feedback via a protocol to the communication infrastructure department.

[0118] Step 6:

[0119] The device notifies the user based on promotional information received from the server. The input is promotional information from the server, and the output is a notification message displayed on the user's screen. The device displays the notification in a pop-up format to attract the user's attention.

[0120] Step 7:

[0121] Users check the display on their device and use promotions as needed. Input is notification messages from the device, and output is user actions such as coupon redemption. When users use promotions at specific shops or services, they can provide feedback through the application.

[0122] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0123] As an embodiment of the present invention, a system is constructed with a server at its core and incorporating an emotion engine that recognizes user emotions. The system collects information on geographical areas where users gather and analyzes it using the emotion engine to reflect the emotional data in the evaluation of the area. Through this emotion analysis, the server quantifies the evaluation of the area and compares it with the infrastructure information of the telecommunications carrier to deliver optimal communication services and promotional information.

[0124] Specifically, the server uses its emotion engine to recognize emotional patterns in text and audio data based on the collected information, and analyzes the convenience and popularity of the area. For example, if there are many positive reviews related to a tourist destination, and these reviews contain many emotions such as "fun" and "satisfied," the server will assign a high numerical rating to that area.

[0125] To deliver promotional information based on users' emotional patterns in highly-rated areas, the server optimizes the content of promotions based on emotional data. For example, users with a specific emotional pattern can be offered music or video content that matches their emotions as a coupon.

[0126] Furthermore, if a server has insufficient coverage in a highly-rated area, sentiment data will be taken into account in the maintenance proposal report. Maintenance proposals will also incorporate elements and requests that users perceive positively, and plans will be made to improve the communication infrastructure. This report will more accurately reflect user needs through sentiment recognition, increasing its value in actual maintenance decisions.

[0127] In this way, by improving network services and optimizing promotions while taking user emotions into consideration, we provide a system that enhances the user experience and contributes to the sustainable value creation of telecommunications carriers.

[0128] The following describes the processing flow.

[0129] Step 1:

[0130] The server collects information about geographical areas from online data sources. Specifically, the server retrieves posts and comments related to a particular area through social media APIs. It also collects word-of-mouth information about an area from review sites and stores it in a database.

[0131] Step 2:

[0132] The server analyzes the data collected using an emotion engine to recognize the user's emotional patterns. Specifically, the server uses natural language processing algorithms to extract emotional expressions from the text. This allows it to calculate emotional scores such as positive, negative, and neutral.

[0133] Step 3:

[0134] The server quantifies the area's evaluation based on sentiment scores. Specifically, it calculates the average of the sentiment scores and records it as the area's evaluation. This evaluation can be compared with other area information as a quantified indicator.

[0135] Step 4:

[0136] The server compares area assessments with the telecommunications carrier's infrastructure information. Specifically, it uses equipment data to verify whether existing network coverage is adequately provided in areas with high assessments.

[0137] Step 5:

[0138] Based on the matching results, the server delivers promotional information optimized for mobile devices within the area. For example, it sends content and offers that are particularly appealing to users who exhibit positive emotions. This is received as a notification on the user's mobile device.

[0139] Step 6:

[0140] The server generates reports that utilize sentiment data to propose improvements for high-rated areas with insufficient coverage. Specifically, the reports reflect the emotional experiences and communication service improvement needs that users desire. These reports are submitted to relevant departments within the company to support decision-making regarding network improvements.

[0141] (Example 2)

[0142] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0143] Traditional methods of providing communication services and promotions have failed to adequately optimize services while considering user emotions, making it difficult to improve the user experience. Furthermore, in the development of regional communication infrastructure, it has been impossible to formulate improvement plans that reflect actual user needs and emotions, resulting in inefficient infrastructure development.

[0144] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0145] In this invention, the server includes means for collecting information about areas where users gather, means for performing sentiment analysis on the collected information using a generating AI model and quantifying the evaluation of the area, and means for delivering promotional information optimized based on sentiment patterns to mobile terminals in the relevant area. This makes it possible to provide services that take users' emotions into consideration, and enables the optimization of promotions and the effective planning of communication infrastructure.

[0146] A "user" is an individual or group that utilizes an information system.

[0147] "Region" refers to a specific geographical area, and the scope within which user information related to that area is collected.

[0148] "Information" refers to data collected from users, including text, audio, location data, and social media posts.

[0149] A "generative AI model" is an algorithm or program that uses artificial intelligence to analyze data and recognize user emotions and other patterns.

[0150] "Emotional analysis" is the process of identifying emotional patterns from collected information and tagging them as positive or negative emotions.

[0151] "Quantification" is the process of converting extractive or analytical data into a quantitative format, thereby facilitating comparison and evaluation.

[0152] A "mobile device" is an electronic device that an individual can carry and connect to a communication network.

[0153] "Promotional information" refers to advertisements and offers provided based on specific areas or user emotional patterns, designed to encourage the use of a service.

[0154] "Emotional patterns" refer to a set of emotional tendencies and characteristics that can be recognized from a user's posts and actions.

[0155] "Communication infrastructure" is a general term for the hardware and software that constitute the equipment and foundations that enable voice and data communication.

[0156] This invention provides a system that performs regional evaluation and promotional optimization by collecting and analyzing user emotions. The server, terminal, and user each play crucial roles in the implementation of this system.

[0157] The server is the core component that centrally collects and processes information within a geographical area. The server has an interface for collecting user-generated content, including text and audio data, and performs sentiment analysis on this content using a generative AI model. Sentiment analysis utilizes natural language processing algorithms and speech recognition technology. Specific software components include a sentiment analysis engine and a database management system. Based on the analysis results, the server quantifies the evaluation of a region. For example, tourist destinations with many positive emotions such as "fun" and "satisfied" receive higher ratings.

[0158] The terminal functions as a device for user interaction. User location information and posted data are sent to the server via the terminal, and sentiment analysis is performed in real time. This data is also used to optimize promotional information, delivering content that matches the user's emotional patterns. For example, a user who wants to relax might be offered a coupon for relaxation music.

[0159] Users are the entities that contribute data to the system through their devices by posting emotionally expressive content on social media and other platforms. This user behavioral data can be used to quantify positive impacts in specific regions and inform the development of communication infrastructure and promotional strategies.

[0160] For example, if user posts about a tourist destination contain many words like "fun" and "amazing," it can raise the region's rating and strengthen the promotion of travel packages. A simple example of a prompt for a generative AI model would be text such as, "Analyze the positive reviews about this area and quantify its popularity based on that content."

[0161] The system provided by this embodiment enables service improvements that take user emotions into consideration, facilitates efficient promotion by telecommunications carriers, and facilitates sustainable value creation.

[0162] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0163] Step 1:

[0164] Users take photos in their daily lives and at places they visit, and post comments and reviews on social media. This allows users to generate information about geographical areas and provide it in a digitized format. In this step, data including the user's location and emotions is generated as input.

[0165] Step 2:

[0166] The device collects user-generated data and sends it to the server. This process includes location information and text data. The input for this step is raw data provided by the user, and the output is data converted to a format suitable for the server. Pre-filtering necessary for sentiment analysis may also be performed.

[0167] Step 3:

[0168] The server receives data sent from the terminal. Using a generative AI model, it analyzes emotions from text and audio. This analysis includes recognizing emotional patterns using natural language processing techniques and tagging positive and negative emotions. The input is data received from the terminal, and the output is analyzed emotional data.

[0169] Step 4:

[0170] The server evaluates geographical areas based on the results of sentiment analysis and quantifies that evaluation. For example, if a tourist destination is filled with positive comments, its evaluation score will be high. In this step, sentiment analysis data is the input, and a multidimensional evaluation score is the output. This evaluation serves as an indicator of the convenience and popularity of the region.

[0171] Step 5:

[0172] The server matches quantified area evaluations with infrastructure information from telecommunications carriers to design optimal promotional information. It generates coupons for music and video content of interest to users with specific emotional patterns. In this step, area evaluations and communication infrastructure data are input, and an emotionally adaptive promotional strategy is output.

[0173] Step 6:

[0174] The server generates a report proposing improvements to communication infrastructure if coverage is potentially lacking in highly-rated areas. By incorporating user sentiment data, the improvement proposals become more realistic and effective. Inputs are area ratings and sentiment data, and the output is a direct improvement proposal report.

[0175] Through this processing step, the system gains the ability to accurately understand the user's emotions and provide optimal network services and promotional information.

[0176] (Application Example 2)

[0177] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as a "server" and the smart device 14 as a "terminal".

[0178] In smart cities, there is a lack of means to help residents and visitors accurately understand the convenience and popularity of different areas within the city and choose the best places to spend their time. Furthermore, there is a need to improve the overall user experience of the city through the optimization of communication infrastructure and the provision of real-time information to residents.

[0179] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0180] In this invention, the server includes a device for collecting information about the geographical area where users gather, a device for analyzing the collected information and quantifying the evaluation of the area, and a device for providing sentiment analysis data about the area surrounding the user in real time. As a result, residents of a smart city can obtain real-time evaluation information about the area, thereby improving the user experience of the city.

[0181] A "user" is an individual or group that uses the system.

[0182] A "geographical area" is a specific physical area where information is collected and evaluated.

[0183] "Information-collecting devices" refer to hardware or software used to acquire data related to geographical areas.

[0184] A "device for analyzing information and quantifying evaluations" is a system for analyzing collected information and performing quantitative evaluations.

[0185] A "communications provider" is a company or business that provides communication services.

[0186] A "device for distributing sales promotion information" is a system that transmits the content of advertisements and promotions to users within the relevant area.

[0187] A "device that outputs proposals regarding maintenance" is a system for presenting areas for improvement and construction plans within a geographical area.

[0188] "Sentiment analysis data" refers to the results of analyzing emotions from user feedback and comments.

[0189] A "device that provides information in real time" is a platform for instantly transmitting the latest information to users.

[0190] A "mobile terminal" is a device with communication capabilities that a user can carry with them.

[0191] A "report generation device" is a system that compiles analysis results and evaluation information into a document.

[0192] To implement this invention, the server needs to be equipped with a device that collects and analyzes information about users' emotions and movements within a geographical area. Users receive emotion data about the area in real time using smartphones or other mobile devices. This system is built using programming languages ​​such as Python or Node.js, and employs natural language processing libraries such as TENSORFLOW® or PyTorch for emotion analysis. Based on these analysis results, the server presents appropriate sales promotion information and area evaluations to residents and visitors.

[0193] For example, if a tourist destination receives a large amount of positive feedback, the server can rate that area highly and offer special events or discounts to tourists. This allows tourists to choose places they will enjoy more and make the most of their visit. An example of a prompt the server might use in this process is, "Please tell me the latest sentiment trends in this area."

[0194] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0195] Step 1:

[0196] The server collects user movement and sentiment data from geographical areas. Inputs include location information and text data obtained from smartphones and various sensors. The server stores the received data in a database and prepares it for analysis.

[0197] Step 2:

[0198] The server inputs the collected data into the sentiment analysis engine and assigns sentiment labels. Sentiment analysis uses TensorFlow to perform natural language processing on the data, associating sentiment values ​​such as positive, negative, and neutral with each text data point. The output is the sentiment label associated with each data point.

[0199] Step 3:

[0200] The server quantifies sentiment labels and aggregates them by geographical region. It averages or aggregates the input sentiment data across each region and generates a region evaluation score based on this. This process uses a Python data aggregation script. The output is the evaluation score for each region.

[0201] Step 4:

[0202] The server determines relevant sales promotion information for each area based on the evaluation score. For areas with high evaluation scores, it selects positive promotional campaigns; for areas with low scores, it selects information including improvement suggestions. The selected information is then entered into the sales promotion campaign service within the server.

[0203] Step 5:

[0204] The terminal displays evaluation scores and sales promotion information received from the server in real time to the user. The terminal uses GPS functionality to determine the user's current location and displays information about the corresponding area on the user interface. This allows the user to visually check the area's evaluation and related event information.

[0205] 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 audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating 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 audio data.

[0206] Data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of data generation model 58 is ChatGPT (registered trademark) (Internet search).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0207] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart device 14.

[0208] [Second Embodiment]

[0209] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0210] As shown in Figure 3, the data processing system 210 includes a data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0211] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0212] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication interface 44. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, and camera 42 are also connected to the bus 52.

[0213] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0214] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0215] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0216] Figure 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Figure 4, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0217] The specific processing program 56 is an example of a "program" relating to the technology of this 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.

[0218] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0219] In the smart glasses 214, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. 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 processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0220] Next, the identification processing performed by the identification processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0221] The embodiments for implementing the present invention will be described focusing on the server, terminal, and user. The invention utilizes a system that collects, analyzes, and verifies information regarding the geographical areas where users gather, distributes promotional information, and generates maintenance suggestions. The server operates as the core of this system.

[0222] The server first collects reviews and ratings information about an area from online data sources. This data is obtained using APIs from social media, review sites, etc., and stored in a database. For example, rating data for a particular tourist spot can be obtained from a specific rating site.

[0223] Next, the server analyzes the collected data. It analyzes the data obtained using natural language processing technology and quantifies the evaluation of specific areas based on that analysis. As a result of the analysis, it becomes possible to identify areas with high ratings, for example.

[0224] The server compares the analyzed evaluation information with the infrastructure information of the communication network. This information includes the location of base stations and frequency bands. Based on the comparison results, the server evaluates the quality of communication services in each area.

[0225] If a highly-rated area has adequate network coverage, the server will deliver promotional information to mobile devices in that area. This promotional information may include data discount coupons or advertising messages. For example, a coupon offering limited-time additional data usage might be sent to users in a specific area.

[0226] On the other hand, for areas with high ratings but insufficient network coverage, the server generates improvement proposals. This is fed back to the company's communications infrastructure department as a report showing the area's value. This feedback report includes area evaluations, analysis of user flow patterns, and potential measures to improve communications services.

[0227] In this way, we can improve the value of services for users and provide a system that efficiently utilizes communication network resources.

[0228] The following describes the processing flow.

[0229] Step 1:

[0230] The server collects information about geographical areas. Specifically, the server retrieves data from publicly available online data sources, such as social media and review sites, using APIs. This is a process of collecting relevant reviews and ratings based on specific keywords and location information.

[0231] Step 2:

[0232] The server analyzes the collected information to quantify the area's evaluation. Specifically, the server uses natural language processing algorithms to analyze the word-of-mouth text, extracting positive or negative words to generate a score. This score is used as the evaluation of that area.

[0233] Step 3:

[0234] The server compares the analyzed evaluation data with information on the infrastructure of the communication network. Specifically, it compares the quantified evaluation of each geographical area with base station and frequency data held by the telecommunications carrier. This allows it to determine whether the network coverage in areas with high evaluations is sufficient.

[0235] Step 4:

[0236] The server delivers promotional information to mobile devices in high-rated areas with sufficient coverage. Specifically, the server sends promotional content via app notifications and SMS to user devices registered in those areas. This includes, for example, coupon information for additional data usage.

[0237] Step 5:

[0238] The server generates improvement proposals for areas with insufficient coverage. Specifically, the server creates reports based on area evaluations and user flow data, and presents them to the internal infrastructure department to recommend network improvement measures for those areas. This feedback supports future base station development and frequency allocation decision-making.

[0239] (Example 1)

[0240] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0241] Traditional communication services, despite having a high reputation in areas where users congregate, sometimes fail to provide adequate network coverage. Furthermore, they struggle to effectively deliver region-specific promotional information to users. This results in a compromised user experience and makes optimizing the communication environment difficult.

[0242] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0243] In this invention, the server includes means for collecting data on areas where users gather, means for quantifying the evaluation of the area using natural language processing technology based on the collected data, and means for comparing the evaluation information of the area with network equipment data of a telecommunications company. This makes it possible to provide optimal communication services to highly-rated areas and to deliver effective promotional information to users.

[0244] "Users" refer to individual people who use information services.

[0245] "Region" refers to a specific geographical area, which is the location where communication services are evaluated.

[0246] "Data" refers to materials containing information, and in this context, it refers to user reviews and information about network equipment.

[0247] "Means of collection" refers to methods or devices used to acquire data about the areas where users gather.

[0248] "Natural language processing technology" refers to the technology that enables computers to understand and analyze human language.

[0249] "Methods for quantifying evaluation" refer to methods of expressing the appeal and quality of a region numerically using analyzed information.

[0250] "Means of matching" refers to techniques or methods for verifying the consistency or relevance between different data.

[0251] "Advertising information" refers to promotional messages about specific products or services.

[0252] A "telecommunications company" refers to a company that provides telecommunications services.

[0253] "Network equipment data" refers to information about communication infrastructure such as base stations and frequency bands.

[0254] To implement this invention, a system in which a server plays a central role is utilized. The server collects and analyzes various data and provides appropriate communication services and promotional information to the areas where users are concentrated.

[0255] First, the server collects review and rating data about a region from online data sources. APIs from social media and review sites on the internet are used for this collection. This data is stored in a database in JSON format. A specific example is obtaining the reputation of a tourist destination from a particular review site.

[0256] The server then applies natural language processing techniques to the collected data. Open-source natural language processing libraries (such as NLTK or SpaCy) are used to analyze the acquired reviews and ratings, quantifying the region's evaluation. This analysis makes it possible to identify regions with high ratings.

[0257] Next, the server compares the regional evaluation information with the infrastructure information of the communication network. This comparison uses GIS data, combining the communication carrier's base station information, frequency bands, and regional evaluations to assess the communication service quality in each area. Based on this evaluation, the server sends promotional information to the user's device. For example, it could distribute offers such as "20% extra data this weekend only" to the user's mobile device.

[0258] For areas with high ratings but insufficient network coverage, the server generates a report with improvement suggestions. This report includes the region's rating score, user behavior patterns, and improvement proposals, and is fed back to the company's communications infrastructure department. This aims to improve both the communication environment and the user experience.

[0259] As an example of a prompt for input to the generating AI model, "Create suggestions for improving communication quality based on user evaluation data in a specific region." This allows for the efficient and effective provision of services optimized for each region.

[0260] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0261] Step 1:

[0262] The server collects local review and word-of-mouth data from social media and review sites on the internet via APIs. It takes user posts and ratings as input and stores them in a database in JSON format. The output at this stage is a set of structured text data.

[0263] Step 2:

[0264] The server analyzes the collected data using a natural language processing library. The input is the word-of-mouth data collected in step 1. Specifically, the server analyzes the text and executes an algorithm that quantifies the positive and negative tendencies of the ratings. The output is the rating score for each region.

[0265] Step 3:

[0266] The server compares the analyzed evaluation scores with information on the infrastructure of the communication network. The inputs are regional evaluation scores and network equipment data such as base station information. Specifically, GIS data is used to compare this data and evaluate the communication service quality for each region. The output is a communication quality report for each area.

[0267] Step 4:

[0268] The server sends promotional information to mobile devices only if there is adequate network coverage in a highly-rated area. The input is the quality report and promotional information obtained in step 3. Specifically, the server delivers advertisements and coupons to the device using push notifications. The output is the promotional message displayed on the user's device.

[0269] Step 5:

[0270] The server generates improvement suggestion reports for areas with a high rating of insufficient network coverage. Inputs include communication quality reports and analyzed user behavior data. Specifically, it considers improvement measures and creates a report for feedback to the communication infrastructure department. The output is the improvement suggestion report.

[0271] (Application Example 1)

[0272] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0273] In cities and tourist destinations, there is a need to maximize the appeal of the region and improve user satisfaction. Furthermore, communication service providers need information to understand the communication quality of the region and provide appropriate services. However, until now, there has been a lack of means to comprehensively analyze detailed regional evaluation information and the state of communication infrastructure to provide effective information and services to users.

[0274] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0275] In this invention, the server includes means for acquiring information about areas where users gather, means for analyzing the acquired information and quantifying the evaluation of the area, and means for comparing the evaluation of the area with the basic equipment information of the communication service provider. This makes it possible to effectively transmit promotional information according to the communication coverage status based on the evaluation information of the area, and to generate improvement suggestions based on feedback from users.

[0276] "Users" refer to individuals or groups who utilize this system and are the recipients of relevant information and services within a specific geographical area.

[0277] A "region" refers to a specific geographical area, such as a tourist destination or a city, where people gather and engage in activities.

[0278] "Means of acquiring information" refers to the processes and techniques for collecting relevant information using online data sources such as social media and review sites.

[0279] "Basic equipment information" refers to data related to the infrastructure of the communication network used by communication service providers, including the location of base stations and frequency bands.

[0280] The "means for transmitting promotion information" refers to communication means or technologies for distributing appropriate promotion information to the user's mobile communication device.

[0281] The "means for generating improvement proposals" refers to systems or methods for analyzing regional evaluation information and user feedback to automatically create improvement measures for communication coverage and various proposals.

[0282] "Evaluation information" refers to evaluations obtained by quantitatively or qualitatively analyzing opinions such as user word-of-mouth and reviews regarding a specific region.

[0283] A "mobile communication device" is a portable communication device that can communicate while in motion, such as a smartphone or tablet.

[0284] The system for realizing this invention is configured around three elements: a server, a terminal, and a user. The server obtains data related to a region online from social media and review sites. Specifically, it collects word-of-mouth and evaluation information via an AP and stores it in a database. The acquired information is analyzed using natural language processing technology on the server (for example, the NLTK library in Python). As a result, the evaluation of a specific region is quantified.

[0285] This analysis result is collated with the infrastructure information held by the communication service provider. The infrastructure information includes data related to the location of base stations and frequency bands. Through this collation, the communication quality of the region is evaluated. And when an appropriate communication service is provided in a region with a high evaluation, the server transmits promotion information to the terminal. This promotion information includes discount coupons for data communication and advertising messages, etc. The terminal receives this and notifies the user.

[0286] On the other hand, in the case of an area with high evaluation but insufficient communication coverage, the server generates an improvement proposal. This proposal is sent to the communication infrastructure department as a report indicating the value of the area. This report includes the evaluation of the area and the results of the analysis of user movement patterns, and shows potential communication service improvement measures such as lubricating oil.

[0287] As a specific example, a user in the urban area can receive map information of the corresponding area and coupons for tourist attractions related thereto on the smartphone during travel. Also, in the shopping area frequently visited by the user, discount information can be automatically received.

[0288] As an example of a prompt sentence for the generation AI model, a sentence such as "Please tell me the popular areas of a specific city and the highly evaluated tourist spots related to those areas." can be cited.

[0289] The flow of the specific process in Application Example 1 will be described using FIG. 12.

[0290] Step 1:

[0291] The server acquires word-of-mouth information and evaluation information related to the area from an online data source (such as an API). In this process, data is automatically collected from social media and review sites. The input is a URL or an API key, etc., and the output is raw text data. The server receives these data and stores them in the database.

[0292] Step 2:

[0293] The server analyzes the collected text data using natural language processing (NLP) technology. Specifically, text summarization and keyword extraction are performed. The input of this process is the raw text data of Step 1, and the output is quantified evaluation data. Using NLTK or other NLP libraries, sentiment analysis of the text is performed to quantify the reputation of the area.

[0294] Step 3:

[0295] The server compares the analyzed evaluation data with communication infrastructure equipment information. This process uses base station location data and frequency band data as input. The output is a communication quality evaluation for each region. The server evaluates communication coverage for each region and determines whether there are any deficiencies.

[0296] Step 4:

[0297] The server sends promotional information to terminals in areas with good communication quality. The input consists of evaluation data and promotional content obtained in step 3, while the output is coupons and messages sent to user terminals. The server generates promotional data and sends it to terminals via the distribution system.

[0298] Step 5:

[0299] The server generates a report indicating areas with insufficient communication coverage that require improvement. The input is the communication evaluation data and user behavior data from step 3, and the output is an improvement suggestion report. The server creates the report and provides feedback via a protocol to the communication infrastructure department.

[0300] Step 6:

[0301] The device notifies the user based on promotional information received from the server. The input is promotional information from the server, and the output is a notification message displayed on the user's screen. The device displays the notification in a pop-up format to attract the user's attention.

[0302] Step 7:

[0303] The user checks the display of the terminal and uses the promotion as needed. The input is a notification message from the terminal, and the output is the user's action such as using a coupon. When the user uses a promotion at a specific shop or service, the information can be fed back through the application.

[0304] Furthermore, an emotion engine for estimating the user's emotion may be combined. That is, the specific processing unit 290 may estimate the user's emotion using the emotion recognition model 59 and perform specific processing using the user's emotion.

[0305] As a form for implementing the present invention, a system incorporating an emotion engine for recognizing the user's emotion is constructed with a server at the core. The system collects information on the geographical area where users gather, and by performing analysis using the emotion engine, reflects the emotion data in the evaluation of the area. Through this emotion analysis, the server quantifies the evaluation of the area and collates it with the infrastructure information of the communication carrier to deliver the optimal communication service and promotion information.

[0306] Specifically, based on the collected information, the server uses the emotion engine to recognize the emotion pattern of text and voice data and analyzes the convenience and popularity of the area. For example, when there are a large number of positive reviews related to a certain tourist destination and the content contains many emotions such as "fun" and "satisfied", the server numerically evaluates the area highly.

[0307] In order to deliver promotion information based on the user's emotion pattern in areas with high evaluations, the server optimizes the content of the promotion according to the emotion data. For example, it is possible to provide music or video content matching the emotion as a coupon to users with a specific emotion pattern.

[0308] Furthermore, if a server has insufficient coverage in a highly-rated area, sentiment data will be taken into account in the maintenance proposal report. Maintenance proposals will also incorporate elements and requests that users perceive positively, and plans will be made to improve the communication infrastructure. This report will more accurately reflect user needs through sentiment recognition, increasing its value in actual maintenance decisions.

[0309] In this way, by improving network services and optimizing promotions while taking user emotions into consideration, we provide a system that enhances the user experience and contributes to the sustainable value creation of telecommunications carriers.

[0310] The following describes the processing flow.

[0311] Step 1:

[0312] The server collects information about geographical areas from online data sources. Specifically, the server retrieves posts and comments related to a particular area through social media APIs. It also collects word-of-mouth information about an area from review sites and stores it in a database.

[0313] Step 2:

[0314] The server analyzes the data collected using an emotion engine to recognize the user's emotional patterns. Specifically, the server uses natural language processing algorithms to extract emotional expressions from the text. This allows it to calculate emotional scores such as positive, negative, and neutral.

[0315] Step 3:

[0316] The server quantifies the area's evaluation based on sentiment scores. Specifically, it calculates the average of the sentiment scores and records it as the area's evaluation. This evaluation can be compared with other area information as a quantified indicator.

[0317] Step 4:

[0318] The server compares area assessments with the telecommunications carrier's infrastructure information. Specifically, it uses equipment data to verify whether existing network coverage is adequately provided in areas with high assessments.

[0319] Step 5:

[0320] Based on the matching results, the server delivers promotional information optimized for mobile devices within the area. For example, it sends content and offers that are particularly appealing to users who exhibit positive emotions. This is received as a notification on the user's mobile device.

[0321] Step 6:

[0322] The server generates reports that utilize sentiment data to propose improvements for high-rated areas with insufficient coverage. Specifically, the reports reflect the emotional experiences and communication service improvement needs that users desire. These reports are submitted to relevant departments within the company to support decision-making regarding network improvements.

[0323] (Example 2)

[0324] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0325] Traditional methods of providing communication services and promotions have failed to adequately optimize services while considering user emotions, making it difficult to improve the user experience. Furthermore, in the development of regional communication infrastructure, it has been impossible to formulate improvement plans that reflect actual user needs and emotions, resulting in inefficient infrastructure development.

[0326] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0327] In this invention, the server includes means for collecting information about areas where users gather, means for performing sentiment analysis on the collected information using a generating AI model and quantifying the evaluation of the area, and means for delivering promotional information optimized based on sentiment patterns to mobile terminals in the relevant area. This makes it possible to provide services that take users' emotions into consideration, and enables the optimization of promotions and the effective planning of communication infrastructure.

[0328] A "user" is an individual or group that utilizes an information system.

[0329] "Region" refers to a specific geographical area, and the scope within which user information related to that area is collected.

[0330] "Information" refers to data collected from users, including text, audio, location data, and social media posts.

[0331] A "generative AI model" is an algorithm or program that uses artificial intelligence to analyze data and recognize user emotions and other patterns.

[0332] "Emotional analysis" is the process of identifying emotional patterns from collected information and tagging them as positive or negative emotions.

[0333] "Quantification" is the process of converting extractive or analytical data into a quantitative format, thereby facilitating comparison and evaluation.

[0334] A "mobile device" is an electronic device that an individual can carry and connect to a communication network.

[0335] "Promotional information" refers to advertisements and offers provided based on specific areas or user emotional patterns, designed to encourage the use of a service.

[0336] "Emotional patterns" refer to a set of emotional tendencies and characteristics that can be recognized from a user's posts and actions.

[0337] "Communication infrastructure" is a general term for the hardware and software that constitute the equipment and foundations that enable voice and data communication.

[0338] This invention provides a system that performs regional evaluation and promotional optimization by collecting and analyzing user emotions. The server, terminal, and user each play crucial roles in the implementation of this system.

[0339] The server is the core component that centrally collects and processes information within a geographical area. The server has an interface for collecting user-generated content, including text and audio data, and performs sentiment analysis on this content using a generative AI model. Sentiment analysis utilizes natural language processing algorithms and speech recognition technology. Specific software components include a sentiment analysis engine and a database management system. Based on the analysis results, the server quantifies the evaluation of a region. For example, tourist destinations with many positive emotions such as "fun" and "satisfied" receive higher ratings.

[0340] The terminal functions as a device for user interaction. User location information and posted data are sent to the server via the terminal, and sentiment analysis is performed in real time. This data is also used to optimize promotional information, delivering content that matches the user's emotional patterns. For example, a user who wants to relax might be offered a coupon for relaxation music.

[0341] Users are the entities that contribute data to the system through their devices by posting emotionally expressive content on social media and other platforms. This user behavioral data can be used to quantify positive impacts in specific regions and inform the development of communication infrastructure and promotional strategies.

[0342] For example, if user posts about a tourist destination contain many words like "fun" and "amazing," it can raise the region's rating and strengthen the promotion of travel packages. A simple example of a prompt for a generative AI model would be text such as, "Analyze the positive reviews about this area and quantify its popularity based on that content."

[0343] The system provided by this embodiment enables service improvements that take user emotions into consideration, facilitates efficient promotion by telecommunications carriers, and facilitates sustainable value creation.

[0344] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0345] Step 1:

[0346] Users take photos in their daily lives and at places they visit, and post comments and reviews on social media. This allows users to generate information about geographical areas and provide it in a digitized format. In this step, data including the user's location and emotions is generated as input.

[0347] Step 2:

[0348] The device collects user-generated data and sends it to the server. This process includes location information and text data. The input for this step is raw data provided by the user, and the output is data converted to a format suitable for the server. Pre-filtering necessary for sentiment analysis may also be performed.

[0349] Step 3:

[0350] The server receives data sent from the terminal. Using a generative AI model, it analyzes emotions from text and audio. This analysis includes recognizing emotional patterns using natural language processing techniques and tagging positive and negative emotions. The input is data received from the terminal, and the output is analyzed emotional data.

[0351] Step 4:

[0352] The server evaluates geographical areas based on the results of sentiment analysis and quantifies that evaluation. For example, if a tourist destination is filled with positive comments, its evaluation score will be high. In this step, sentiment analysis data is the input, and a multidimensional evaluation score is the output. This evaluation serves as an indicator of the convenience and popularity of the region.

[0353] Step 5:

[0354] The server matches quantified area evaluations with infrastructure information from telecommunications carriers to design optimal promotional information. It generates coupons for music and video content of interest to users with specific emotional patterns. In this step, area evaluations and communication infrastructure data are input, and an emotionally adaptive promotional strategy is output.

[0355] Step 6:

[0356] The server generates a report proposing improvements to communication infrastructure if coverage is potentially lacking in highly-rated areas. By incorporating user sentiment data, the improvement proposals become more realistic and effective. Inputs are area ratings and sentiment data, and the output is a direct improvement proposal report.

[0357] Through this processing step, the system gains the ability to accurately understand the user's emotions and provide optimal network services and promotional information.

[0358] (Application Example 2)

[0359] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0360] In smart cities, there is a lack of means to help residents and visitors accurately understand the convenience and popularity of different areas within the city and choose the best places to spend their time. Furthermore, there is a need to improve the overall user experience of the city through the optimization of communication infrastructure and the provision of real-time information to residents.

[0361] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0362] In this invention, the server includes a device for collecting information about the geographical area where users gather, a device for analyzing the collected information and quantifying the evaluation of the area, and a device for providing sentiment analysis data about the area surrounding the user in real time. As a result, residents of a smart city can obtain real-time evaluation information about the area, thereby improving the user experience of the city.

[0363] A "user" is an individual or group that uses the system.

[0364] A "geographical area" is a specific physical area where information is collected and evaluated.

[0365] "Information-collecting devices" refer to hardware or software used to acquire data related to geographical areas.

[0366] A "device for analyzing information and quantifying evaluations" is a system for analyzing collected information and performing quantitative evaluations.

[0367] A "communications provider" is a company or business that provides communication services.

[0368] A "device for distributing sales promotion information" is a system that transmits the content of advertisements and promotions to users within the relevant area.

[0369] A "device that outputs proposals regarding maintenance" is a system for presenting areas for improvement and construction plans within a geographical area.

[0370] "Sentiment analysis data" refers to the results of analyzing emotions from user feedback and comments.

[0371] A "device that provides information in real time" is a platform for instantly transmitting the latest information to users.

[0372] A "mobile terminal" is a device with communication capabilities that a user can carry with them.

[0373] A "report generation device" is a system that compiles analysis results and evaluation information into a document.

[0374] To implement this invention, the server needs to be equipped with a device that collects and analyzes information about users' emotions and movements within a geographical area. Users receive emotion data about the area in real time using smartphones or other mobile devices. This system is built using programming languages ​​such as Python or Node.js, and employs natural language processing libraries such as TensorFlow or PyTorch for emotion analysis. Based on these analysis results, the server presents appropriate sales promotion information and area evaluations to residents and visitors.

[0375] For example, if a tourist destination receives a large amount of positive feedback, the server can rate that area highly and offer special events or discounts to tourists. This allows tourists to choose places they will enjoy more and make the most of their visit. An example of a prompt the server might use in this process is, "Please tell me the latest sentiment trends in this area."

[0376] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0377] Step 1:

[0378] The server collects user movement and sentiment data from geographical areas. Inputs include location information and text data obtained from smartphones and various sensors. The server stores the received data in a database and prepares it for analysis.

[0379] Step 2:

[0380] The server inputs the collected data into the sentiment analysis engine and assigns sentiment labels. Sentiment analysis uses TensorFlow to perform natural language processing on the data, associating sentiment values ​​such as positive, negative, and neutral with each text data point. The output is the sentiment label associated with each data point.

[0381] Step 3:

[0382] The server quantifies sentiment labels and aggregates them by geographical region. It averages or aggregates the input sentiment data across each region and generates a region evaluation score based on this. This process uses a Python data aggregation script. The output is the evaluation score for each region.

[0383] Step 4:

[0384] The server determines relevant sales promotion information for each area based on the evaluation score. For areas with high evaluation scores, it selects positive promotional campaigns; for areas with low scores, it selects information including improvement suggestions. The selected information is then entered into the sales promotion campaign service within the server.

[0385] Step 5:

[0386] The terminal displays evaluation scores and sales promotion information received from the server in real time to the user. The terminal uses GPS functionality to determine the user's current location and displays information about the corresponding area on the user interface. This allows the user to visually check the area's evaluation and related event information.

[0387] 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 audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0388] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0389] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart glasses 214.

[0390] [Third Embodiment]

[0391] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0392] As shown in Figure 5, the data processing system 310 includes a data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0393] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0394] The headset terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a display 343. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and display 343 are also connected to the bus 52.

[0395] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0396] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0397] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0398] Figure 6 shows an example of the main functions of the data processing device 12 and the headset terminal 314. As shown in Figure 6, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0399] The specific processing program 56 is an example of a "program" relating to the technology of this 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.

[0400] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0401] In the headset terminal 314, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. 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 processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0402] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the headset terminal 314 will be referred to as the "terminal".

[0403] The embodiments for implementing the present invention will be described focusing on the server, terminal, and user. The invention utilizes a system that collects, analyzes, and verifies information regarding the geographical areas where users gather, distributes promotional information, and generates maintenance suggestions. The server operates as the core of this system.

[0404] The server first collects reviews and ratings information about an area from online data sources. This data is obtained using APIs from social media, review sites, etc., and stored in a database. For example, rating data for a particular tourist spot can be obtained from a specific rating site.

[0405] Next, the server analyzes the collected data. It analyzes the data obtained using natural language processing technology and quantifies the evaluation of specific areas based on that analysis. As a result of the analysis, it becomes possible to identify areas with high ratings, for example.

[0406] The server compares the analyzed evaluation information with the infrastructure information of the communication network. This information includes the location of base stations and frequency bands. Based on the comparison results, the server evaluates the quality of communication services in each area.

[0407] If a highly-rated area has adequate network coverage, the server will deliver promotional information to mobile devices in that area. This promotional information may include data discount coupons or advertising messages. For example, a coupon offering limited-time additional data usage might be sent to users in a specific area.

[0408] On the other hand, for areas with high ratings but insufficient network coverage, the server generates improvement proposals. This is fed back to the company's communications infrastructure department as a report showing the area's value. This feedback report includes area evaluations, analysis of user flow patterns, and potential measures to improve communications services.

[0409] In this way, we can improve the value of services for users and provide a system that efficiently utilizes communication network resources.

[0410] The following describes the processing flow.

[0411] Step 1:

[0412] The server collects information about geographical areas. Specifically, the server retrieves data from publicly available online data sources, such as social media and review sites, using APIs. This is a process of collecting relevant reviews and ratings based on specific keywords and location information.

[0413] Step 2:

[0414] The server analyzes the collected information to quantify the area's evaluation. Specifically, the server uses natural language processing algorithms to analyze the word-of-mouth text, extracting positive or negative words to generate a score. This score is used as the evaluation of that area.

[0415] Step 3:

[0416] The server compares the analyzed evaluation data with information on the infrastructure of the communication network. Specifically, it compares the quantified evaluation of each geographical area with base station and frequency data held by the telecommunications carrier. This allows it to determine whether the network coverage in areas with high evaluations is sufficient.

[0417] Step 4:

[0418] The server delivers promotional information to mobile devices in high-rated areas with sufficient coverage. Specifically, the server sends promotional content via app notifications and SMS to user devices registered in those areas. This includes, for example, coupon information for additional data usage.

[0419] Step 5:

[0420] The server generates improvement proposals for areas with insufficient coverage. Specifically, the server creates reports based on area evaluations and user flow data, and presents them to the internal infrastructure department to recommend network improvement measures for those areas. This feedback supports future base station development and frequency allocation decision-making.

[0421] (Example 1)

[0422] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0423] Traditional communication services, despite having a high reputation in areas where users congregate, sometimes fail to provide adequate network coverage. Furthermore, they struggle to effectively deliver region-specific promotional information to users. This results in a compromised user experience and makes optimizing the communication environment difficult.

[0424] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0425] In this invention, the server includes means for collecting data on areas where users gather, means for quantifying the evaluation of the area using natural language processing technology based on the collected data, and means for comparing the evaluation information of the area with network equipment data of a telecommunications company. This makes it possible to provide optimal communication services to highly-rated areas and to deliver effective promotional information to users.

[0426] "Users" refer to individual people who use information services.

[0427] "Region" refers to a specific geographical area, which is the location where communication services are evaluated.

[0428] "Data" refers to materials containing information, and in this context, it refers to user reviews and information about network equipment.

[0429] "Means of collection" refers to methods or devices used to acquire data about the areas where users gather.

[0430] "Natural language processing technology" refers to the technology that enables computers to understand and analyze human language.

[0431] "Methods for quantifying evaluation" refer to methods of expressing the appeal and quality of a region numerically using analyzed information.

[0432] "Means of matching" refers to techniques or methods for verifying the consistency or relevance between different data.

[0433] "Advertising information" refers to promotional messages about specific products or services.

[0434] A "telecommunications company" refers to a company that provides telecommunications services.

[0435] "Network equipment data" refers to information about communication infrastructure such as base stations and frequency bands.

[0436] To implement this invention, a system in which a server plays a central role is utilized. The server collects and analyzes various data and provides appropriate communication services and promotional information to the areas where users are concentrated.

[0437] First, the server collects review and rating data about a region from online data sources. APIs from social media and review sites on the internet are used for this collection. This data is stored in a database in JSON format. A specific example is obtaining the reputation of a tourist destination from a particular review site.

[0438] The server then applies natural language processing techniques to the collected data. Open-source natural language processing libraries (such as NLTK or SpaCy) are used to analyze the acquired reviews and ratings, quantifying the region's evaluation. This analysis makes it possible to identify regions with high ratings.

[0439] Next, the server compares the regional evaluation information with the infrastructure information of the communication network. This comparison uses GIS data, combining the communication carrier's base station information, frequency bands, and regional evaluations to assess the communication service quality in each area. Based on this evaluation, the server sends promotional information to the user's device. For example, it could distribute offers such as "20% extra data this weekend only" to the user's mobile device.

[0440] For areas with high ratings but insufficient network coverage, the server generates a report with improvement suggestions. This report includes the region's rating score, user behavior patterns, and improvement proposals, and is fed back to the company's communications infrastructure department. This aims to improve both the communication environment and the user experience.

[0441] As an example of a prompt for input to the generating AI model, "Create suggestions for improving communication quality based on user evaluation data in a specific region." This allows for the efficient and effective provision of services optimized for each region.

[0442] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0443] Step 1:

[0444] The server collects local review and word-of-mouth data from social media and review sites on the internet via APIs. It takes user posts and ratings as input and stores them in a database in JSON format. The output at this stage is a set of structured text data.

[0445] Step 2:

[0446] The server analyzes the collected data using a natural language processing library. The input is the word-of-mouth data collected in step 1. Specifically, the server analyzes the text and executes an algorithm that quantifies the positive and negative tendencies of the ratings. The output is the rating score for each region.

[0447] Step 3:

[0448] The server compares the analyzed evaluation scores with information on the infrastructure of the communication network. The inputs are regional evaluation scores and network equipment data such as base station information. Specifically, GIS data is used to compare this data and evaluate the communication service quality for each region. The output is a communication quality report for each area.

[0449] Step 4:

[0450] The server sends promotional information to mobile devices only if there is adequate network coverage in a highly-rated area. The input is the quality report and promotional information obtained in step 3. Specifically, the server delivers advertisements and coupons to the device using push notifications. The output is the promotional message displayed on the user's device.

[0451] Step 5:

[0452] The server generates improvement suggestion reports for areas with a high rating of insufficient network coverage. Inputs include communication quality reports and analyzed user behavior data. Specifically, it considers improvement measures and creates a report for feedback to the communication infrastructure department. The output is the improvement suggestion report.

[0453] (Application Example 1)

[0454] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0455] In cities and tourist destinations, there is a need to maximize the appeal of the region and improve user satisfaction. Furthermore, communication service providers need information to understand the communication quality of the region and provide appropriate services. However, until now, there has been a lack of means to comprehensively analyze detailed regional evaluation information and the state of communication infrastructure to provide effective information and services to users.

[0456] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0457] In this invention, the server includes means for acquiring information about areas where users gather, means for analyzing the acquired information and quantifying the evaluation of the area, and means for comparing the evaluation of the area with the basic equipment information of the communication service provider. This makes it possible to effectively transmit promotional information according to the communication coverage status based on the evaluation information of the area, and to generate improvement suggestions based on feedback from users.

[0458] "Users" refer to individuals or groups who utilize this system and are the recipients of relevant information and services within a specific geographical area.

[0459] A "region" refers to a specific geographical area, such as a tourist destination or a city, where people gather and engage in activities.

[0460] "Means of acquiring information" refers to the processes and techniques for collecting relevant information using online data sources such as social media and review sites.

[0461] "Basic equipment information" refers to data related to the infrastructure of the communication network used by communication service providers, including the location of base stations and frequency bands.

[0462] "Means of transmitting promotional information" refers to communication methods and technologies for delivering appropriate promotional information to users' mobile communication devices.

[0463] "Means for generating improvement proposals" refers to systems and methods for analyzing regional evaluation information and user feedback to automatically create improvement measures and various proposals for communication coverage.

[0464] "Evaluation information" refers to evaluations obtained by quantifying or qualitatively analyzing user opinions such as word-of-mouth and reviews regarding a specific region.

[0465] A "mobile communication device" refers to a portable communication device, such as a smartphone or tablet, that can communicate even while on the move.

[0466] The system for realizing this invention is composed of three main components: a server, a terminal, and a user. The server acquires local data online from social media and review sites. Specifically, it collects word-of-mouth and rating information via AP and stores it in a database. The acquired information is analyzed using natural language processing technology on the server (for example, Python's NLTK library). As a result, the rating of a particular region is quantified.

[0467] The server then compares the analysis results with the basic equipment information held by the communication service provider. This basic equipment information includes data on base station locations and frequency bands. This comparison allows for an evaluation of the communication quality in the area. If a suitable communication service is provided in an area with a high evaluation, the server transmits promotional information to the terminal. This promotional information includes data communication discount coupons and advertising messages. The terminal receives this information and notifies the user.

[0468] On the other hand, in areas with high ratings but insufficient communication coverage, the server generates improvement suggestions. These suggestions are sent to the communications infrastructure department as a report highlighting the area's value. This report includes the results of the area's evaluation and user flow pattern analysis, and, like a lubricant, indicates potential improvements to communications services.

[0469] For example, users in urban areas can receive map information for their area and coupons for related tourist attractions on their smartphones while traveling. They can also automatically receive discount information for shopping areas they frequently visit.

[0470] An example of a prompt sentence for a generative AI model is, "Please tell me about popular areas in a specific city and highly-rated tourist attractions associated with those areas."

[0471] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0472] Step 1:

[0473] The server retrieves local reviews and ratings from online data sources (such as APIs). This process automatically collects data from social media and review sites. Inputs include URLs and API keys, while output is raw text data. The server receives this data and stores it in a database.

[0474] Step 2:

[0475] The server analyzes the collected text data using natural language processing (NLP) techniques. Specifically, it performs text summarization and keyword extraction. The input to this process is the raw text data from step 1, and the output is quantified evaluation data. Using NLTK or other NLP libraries, sentiment analysis of the text is performed to quantify the reputation of the area.

[0476] Step 3:

[0477] The server compares the analyzed evaluation data with communication infrastructure equipment information. This process uses base station location data and frequency band data as input. The output is a communication quality evaluation for each region. The server evaluates communication coverage for each region and determines whether there are any deficiencies.

[0478] Step 4:

[0479] The server sends promotional information to terminals in areas with good communication quality. The input consists of evaluation data and promotional content obtained in step 3, while the output is coupons and messages sent to user terminals. The server generates promotional data and sends it to terminals via the distribution system.

[0480] Step 5:

[0481] The server generates a report indicating areas with insufficient communication coverage that require improvement. The input is the communication evaluation data and user behavior data from step 3, and the output is an improvement suggestion report. The server creates the report and provides feedback via a protocol to the communication infrastructure department.

[0482] Step 6:

[0483] The device notifies the user based on promotional information received from the server. The input is promotional information from the server, and the output is a notification message displayed on the user's screen. The device displays the notification in a pop-up format to attract the user's attention.

[0484] Step 7:

[0485] Users check the display on their device and use promotions as needed. Input is notification messages from the device, and output is user actions such as coupon redemption. When users use promotions at specific shops or services, they can provide feedback through the application.

[0486] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0487] As an embodiment of the present invention, a system is constructed with a server at its core and incorporating an emotion engine that recognizes user emotions. The system collects information on geographical areas where users gather and analyzes it using the emotion engine to reflect the emotional data in the evaluation of the area. Through this emotion analysis, the server quantifies the evaluation of the area and compares it with the infrastructure information of the telecommunications carrier to deliver optimal communication services and promotional information.

[0488] Specifically, the server uses its emotion engine to recognize emotional patterns in text and audio data based on the collected information, and analyzes the convenience and popularity of the area. For example, if there are many positive reviews related to a tourist destination, and these reviews contain many emotions such as "fun" and "satisfied," the server will assign a high numerical rating to that area.

[0489] To deliver promotional information based on users' emotional patterns in highly-rated areas, the server optimizes the content of promotions based on emotional data. For example, users with a specific emotional pattern can be offered music or video content that matches their emotions as a coupon.

[0490] Furthermore, if a server has insufficient coverage in a highly-rated area, sentiment data will be taken into account in the maintenance proposal report. Maintenance proposals will also incorporate elements and requests that users perceive positively, and plans will be made to improve the communication infrastructure. This report will more accurately reflect user needs through sentiment recognition, increasing its value in actual maintenance decisions.

[0491] In this way, by improving network services and optimizing promotions while taking user emotions into consideration, we provide a system that enhances the user experience and contributes to the sustainable value creation of telecommunications carriers.

[0492] The following describes the processing flow.

[0493] Step 1:

[0494] The server collects information about geographical areas from online data sources. Specifically, the server retrieves posts and comments related to a particular area through social media APIs. It also collects word-of-mouth information about an area from review sites and stores it in a database.

[0495] Step 2:

[0496] The server analyzes the data collected using an emotion engine to recognize the user's emotional patterns. Specifically, the server uses natural language processing algorithms to extract emotional expressions from the text. This allows it to calculate emotional scores such as positive, negative, and neutral.

[0497] Step 3:

[0498] The server quantifies the area's evaluation based on sentiment scores. Specifically, it calculates the average of the sentiment scores and records it as the area's evaluation. This evaluation can be compared with other area information as a quantified indicator.

[0499] Step 4:

[0500] The server compares area assessments with the telecommunications carrier's infrastructure information. Specifically, it uses equipment data to verify whether existing network coverage is adequately provided in areas with high assessments.

[0501] Step 5:

[0502] Based on the matching results, the server delivers promotional information optimized for mobile devices within the area. For example, it sends content and offers that are particularly appealing to users who exhibit positive emotions. This is received as a notification on the user's mobile device.

[0503] Step 6:

[0504] The server generates reports that utilize sentiment data to propose improvements for high-rated areas with insufficient coverage. Specifically, the reports reflect the emotional experiences and communication service improvement needs that users desire. These reports are submitted to relevant departments within the company to support decision-making regarding network improvements.

[0505] (Example 2)

[0506] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0507] Traditional methods of providing communication services and promotions have failed to adequately optimize services while considering user emotions, making it difficult to improve the user experience. Furthermore, in the development of regional communication infrastructure, it has been impossible to formulate improvement plans that reflect actual user needs and emotions, resulting in inefficient infrastructure development.

[0508] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0509] In this invention, the server includes means for collecting information about areas where users gather, means for performing sentiment analysis on the collected information using a generating AI model and quantifying the evaluation of the area, and means for delivering promotional information optimized based on sentiment patterns to mobile terminals in the relevant area. This makes it possible to provide services that take users' emotions into consideration, and enables the optimization of promotions and the effective planning of communication infrastructure.

[0510] A "user" is an individual or group that utilizes an information system.

[0511] "Region" refers to a specific geographical area, and the scope within which user information related to that area is collected.

[0512] "Information" refers to data collected from users, including text, audio, location data, and social media posts.

[0513] A "generative AI model" is an algorithm or program that uses artificial intelligence to analyze data and recognize user emotions and other patterns.

[0514] "Emotional analysis" is the process of identifying emotional patterns from collected information and tagging them as positive or negative emotions.

[0515] "Quantification" is the process of converting extractive or analytical data into a quantitative format, thereby facilitating comparison and evaluation.

[0516] A "mobile device" is an electronic device that an individual can carry and connect to a communication network.

[0517] "Promotional information" refers to advertisements and offers provided based on specific areas or user emotional patterns, designed to encourage the use of a service.

[0518] "Emotional patterns" refer to a set of emotional tendencies and characteristics that can be recognized from a user's posts and actions.

[0519] "Communication infrastructure" is a general term for the hardware and software that constitute the equipment and foundations that enable voice and data communication.

[0520] This invention provides a system that performs regional evaluation and promotional optimization by collecting and analyzing user emotions. The server, terminal, and user each play crucial roles in the implementation of this system.

[0521] The server is the core component that centrally collects and processes information within a geographical area. The server has an interface for collecting user-generated content, including text and audio data, and performs sentiment analysis on this content using a generative AI model. Sentiment analysis utilizes natural language processing algorithms and speech recognition technology. Specific software components include a sentiment analysis engine and a database management system. Based on the analysis results, the server quantifies the evaluation of a region. For example, tourist destinations with many positive emotions such as "fun" and "satisfied" receive higher ratings.

[0522] The terminal functions as a device for user interaction. User location information and posted data are sent to the server via the terminal, and sentiment analysis is performed in real time. This data is also used to optimize promotional information, delivering content that matches the user's emotional patterns. For example, a user who wants to relax might be offered a coupon for relaxation music.

[0523] Users are the entities that contribute data to the system through their devices by posting emotionally expressive content on social media and other platforms. This user behavioral data can be used to quantify positive impacts in specific regions and inform the development of communication infrastructure and promotional strategies.

[0524] For example, if user posts about a tourist destination contain many words like "fun" and "amazing," it can raise the region's rating and strengthen the promotion of travel packages. A simple example of a prompt for a generative AI model would be text such as, "Analyze the positive reviews about this area and quantify its popularity based on that content."

[0525] The system provided by this embodiment enables service improvements that take user emotions into consideration, facilitates efficient promotion by telecommunications carriers, and facilitates sustainable value creation.

[0526] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0527] Step 1:

[0528] Users take photos in their daily lives and at places they visit, and post comments and reviews on social media. This allows users to generate information about geographical areas and provide it in a digitized format. In this step, data including the user's location and emotions is generated as input.

[0529] Step 2:

[0530] The device collects user-generated data and sends it to the server. This process includes location information and text data. The input for this step is raw data provided by the user, and the output is data converted to a format suitable for the server. Pre-filtering necessary for sentiment analysis may also be performed.

[0531] Step 3:

[0532] The server receives data sent from the terminal. Using a generative AI model, it analyzes emotions from text and audio. This analysis includes recognizing emotional patterns using natural language processing techniques and tagging positive and negative emotions. The input is data received from the terminal, and the output is analyzed emotional data.

[0533] Step 4:

[0534] The server evaluates geographical areas based on the results of sentiment analysis and quantifies that evaluation. For example, if a tourist destination is filled with positive comments, its evaluation score will be high. In this step, sentiment analysis data is the input, and a multidimensional evaluation score is the output. This evaluation serves as an indicator of the convenience and popularity of the region.

[0535] Step 5:

[0536] The server matches quantified area evaluations with infrastructure information from telecommunications carriers to design optimal promotional information. It generates coupons for music and video content of interest to users with specific emotional patterns. In this step, area evaluations and communication infrastructure data are input, and an emotionally adaptive promotional strategy is output.

[0537] Step 6:

[0538] The server generates a report proposing improvements to communication infrastructure if coverage is potentially lacking in highly-rated areas. By incorporating user sentiment data, the improvement proposals become more realistic and effective. Inputs are area ratings and sentiment data, and the output is a direct improvement proposal report.

[0539] Through this processing step, the system gains the ability to accurately understand the user's emotions and provide optimal network services and promotional information.

[0540] (Application Example 2)

[0541] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0542] In smart cities, there is a lack of means to help residents and visitors accurately understand the convenience and popularity of different areas within the city and choose the best places to spend their time. Furthermore, there is a need to improve the overall user experience of the city through the optimization of communication infrastructure and the provision of real-time information to residents.

[0543] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0544] In this invention, the server includes a device for collecting information about the geographical area where users gather, a device for analyzing the collected information and quantifying the evaluation of the area, and a device for providing sentiment analysis data about the area surrounding the user in real time. As a result, residents of a smart city can obtain real-time evaluation information about the area, thereby improving the user experience of the city.

[0545] A "user" is an individual or group that uses the system.

[0546] A "geographical area" is a specific physical area where information is collected and evaluated.

[0547] "Information-collecting devices" refer to hardware or software used to acquire data related to geographical areas.

[0548] A "device for analyzing information and quantifying evaluations" is a system for analyzing collected information and performing quantitative evaluations.

[0549] A "communications provider" is a company or business that provides communication services.

[0550] A "device for distributing sales promotion information" is a system that transmits the content of advertisements and promotions to users within the relevant area.

[0551] A "device that outputs proposals regarding maintenance" is a system for presenting areas for improvement and construction plans within a geographical area.

[0552] "Sentiment analysis data" refers to the results of analyzing emotions from user feedback and comments.

[0553] A "device that provides information in real time" is a platform for instantly transmitting the latest information to users.

[0554] A "mobile terminal" is a device with communication capabilities that a user can carry with them.

[0555] A "report generation device" is a system that compiles analysis results and evaluation information into a document.

[0556] To implement this invention, the server needs to be equipped with a device that collects and analyzes information about users' emotions and movements within a geographical area. Users receive emotion data about the area in real time using smartphones or other mobile devices. This system is built using programming languages ​​such as Python or Node.js, and employs natural language processing libraries such as TensorFlow or PyTorch for emotion analysis. Based on these analysis results, the server presents appropriate sales promotion information and area evaluations to residents and visitors.

[0557] For example, if a tourist destination receives a large amount of positive feedback, the server can rate that area highly and offer special events or discounts to tourists. This allows tourists to choose places they will enjoy more and make the most of their visit. An example of a prompt the server might use in this process is, "Please tell me the latest sentiment trends in this area."

[0558] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0559] Step 1:

[0560] The server collects user movement and sentiment data from geographical areas. Inputs include location information and text data obtained from smartphones and various sensors. The server stores the received data in a database and prepares it for analysis.

[0561] Step 2:

[0562] The server inputs the collected data into the sentiment analysis engine and assigns sentiment labels. Sentiment analysis uses TensorFlow to perform natural language processing on the data, associating sentiment values ​​such as positive, negative, and neutral with each text data point. The output is the sentiment label associated with each data point.

[0563] Step 3:

[0564] The server quantifies sentiment labels and aggregates them by geographical region. It averages or aggregates the input sentiment data across each region and generates a region evaluation score based on this. This process uses a Python data aggregation script. The output is the evaluation score for each region.

[0565] Step 4:

[0566] The server determines relevant sales promotion information for each area based on the evaluation score. For areas with high evaluation scores, it selects positive promotional campaigns; for areas with low scores, it selects information including improvement suggestions. The selected information is then entered into the sales promotion campaign service within the server.

[0567] Step 5:

[0568] The terminal displays evaluation scores and sales promotion information received from the server in real time to the user. The terminal uses GPS functionality to determine the user's current location and displays information about the corresponding area on the user interface. This allows the user to visually check the area's evaluation and related event information.

[0569] The specific processing unit 290 transmits the result of the specific processing to the headset terminal 314. In the headset terminal 314, the control unit 46A causes the speaker 240 and display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0570] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0571] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and specific processing may also be performed by the headset terminal 314.

[0572] [Fourth Embodiment]

[0573] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0574] As shown in Figure 7, the data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[0575] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0576] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a controlled object 443. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and controlled object 443 are also connected to the bus 52.

[0577] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0578] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0579] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0580] The controlled object 443 includes a display device, LEDs in the eyes, and motors that drive the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the robot 414's emotions can be expressed by controlling these motors. Furthermore, the robot 414's facial expressions can also be expressed by controlling the illumination state of the LEDs in its eyes.

[0581] Figure 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Figure 8, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0582] The specific processing program 56 is an example of a "program" relating to the technology of this 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.

[0583] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0584] In robot 414, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. 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 processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0585] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0586] The embodiments for implementing the present invention will be described focusing on the server, terminal, and user. The invention utilizes a system that collects, analyzes, and verifies information regarding the geographical areas where users gather, distributes promotional information, and generates maintenance suggestions. The server operates as the core of this system.

[0587] The server first collects reviews and ratings information about an area from online data sources. This data is obtained using APIs from social media, review sites, etc., and stored in a database. For example, rating data for a particular tourist spot can be obtained from a specific rating site.

[0588] Next, the server analyzes the collected data. It analyzes the data obtained using natural language processing technology and quantifies the evaluation of specific areas based on that analysis. As a result of the analysis, it becomes possible to identify areas with high ratings, for example.

[0589] The server compares the analyzed evaluation information with the infrastructure information of the communication network. This information includes the location of base stations and frequency bands. Based on the comparison results, the server evaluates the quality of communication services in each area.

[0590] If a highly-rated area has adequate network coverage, the server will deliver promotional information to mobile devices in that area. This promotional information may include data discount coupons or advertising messages. For example, a coupon offering limited-time additional data usage might be sent to users in a specific area.

[0591] On the other hand, for areas with high ratings but insufficient network coverage, the server generates improvement proposals. This is fed back to the company's communications infrastructure department as a report showing the area's value. This feedback report includes area evaluations, analysis of user flow patterns, and potential measures to improve communications services.

[0592] In this way, we can improve the value of services for users and provide a system that efficiently utilizes communication network resources.

[0593] The following describes the processing flow.

[0594] Step 1:

[0595] The server collects information about geographical areas. Specifically, the server retrieves data from publicly available online data sources, such as social media and review sites, using APIs. This is a process of collecting relevant reviews and ratings based on specific keywords and location information.

[0596] Step 2:

[0597] The server analyzes the collected information to quantify the area's evaluation. Specifically, the server uses natural language processing algorithms to analyze the word-of-mouth text, extracting positive or negative words to generate a score. This score is used as the evaluation of that area.

[0598] Step 3:

[0599] The server compares the analyzed evaluation data with information on the infrastructure of the communication network. Specifically, it compares the quantified evaluation of each geographical area with base station and frequency data held by the telecommunications carrier. This allows it to determine whether the network coverage in areas with high evaluations is sufficient.

[0600] Step 4:

[0601] The server delivers promotional information to mobile devices in high-rated areas with sufficient coverage. Specifically, the server sends promotional content via app notifications and SMS to user devices registered in those areas. This includes, for example, coupon information for additional data usage.

[0602] Step 5:

[0603] The server generates improvement proposals for areas with insufficient coverage. Specifically, the server creates reports based on area evaluations and user flow data, and presents them to the internal infrastructure department to recommend network improvement measures for those areas. This feedback supports future base station development and frequency allocation decision-making.

[0604] (Example 1)

[0605] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0606] Traditional communication services, despite having a high reputation in areas where users congregate, sometimes fail to provide adequate network coverage. Furthermore, they struggle to effectively deliver region-specific promotional information to users. This results in a compromised user experience and makes optimizing the communication environment difficult.

[0607] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0608] In this invention, the server includes means for collecting data on areas where users gather, means for quantifying the evaluation of the area using natural language processing technology based on the collected data, and means for comparing the evaluation information of the area with network equipment data of a telecommunications company. This makes it possible to provide optimal communication services to highly-rated areas and to deliver effective promotional information to users.

[0609] "Users" refer to individual people who use information services.

[0610] "Region" refers to a specific geographical area, which is the location where communication services are evaluated.

[0611] "Data" refers to materials containing information, and in this context, it refers to user reviews and information about network equipment.

[0612] "Means of collection" refers to methods or devices used to acquire data about the areas where users gather.

[0613] "Natural language processing technology" refers to the technology that enables computers to understand and analyze human language.

[0614] "Methods for quantifying evaluation" refer to methods of expressing the appeal and quality of a region numerically using analyzed information.

[0615] "Means of matching" refers to techniques or methods for verifying the consistency or relevance between different data.

[0616] "Advertising information" refers to promotional messages about specific products or services.

[0617] A "telecommunications company" refers to a company that provides telecommunications services.

[0618] "Network equipment data" refers to information about communication infrastructure such as base stations and frequency bands.

[0619] To implement this invention, a system in which a server plays a central role is utilized. The server collects and analyzes various data and provides appropriate communication services and promotional information to the areas where users are concentrated.

[0620] First, the server collects review and rating data about a region from online data sources. APIs from social media and review sites on the internet are used for this collection. This data is stored in a database in JSON format. A specific example is obtaining the reputation of a tourist destination from a particular review site.

[0621] The server then applies natural language processing techniques to the collected data. Open-source natural language processing libraries (such as NLTK or SpaCy) are used to analyze the acquired reviews and ratings, quantifying the region's evaluation. This analysis makes it possible to identify regions with high ratings.

[0622] Next, the server compares the regional evaluation information with the infrastructure information of the communication network. This comparison uses GIS data, combining the communication carrier's base station information, frequency bands, and regional evaluations to assess the communication service quality in each area. Based on this evaluation, the server sends promotional information to the user's device. For example, it could distribute offers such as "20% extra data this weekend only" to the user's mobile device.

[0623] For areas with high ratings but insufficient network coverage, the server generates a report with improvement suggestions. This report includes the region's rating score, user behavior patterns, and improvement proposals, and is fed back to the company's communications infrastructure department. This aims to improve both the communication environment and the user experience.

[0624] As an example of a prompt for input to the generating AI model, "Create suggestions for improving communication quality based on user evaluation data in a specific region." This allows for the efficient and effective provision of services optimized for each region.

[0625] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0626] Step 1:

[0627] The server collects local review and word-of-mouth data from social media and review sites on the internet via APIs. It takes user posts and ratings as input and stores them in a database in JSON format. The output at this stage is a set of structured text data.

[0628] Step 2:

[0629] The server analyzes the collected data using a natural language processing library. The input is the word-of-mouth data collected in step 1. Specifically, the server analyzes the text and executes an algorithm that quantifies the positive and negative tendencies of the ratings. The output is the rating score for each region.

[0630] Step 3:

[0631] The server compares the analyzed evaluation scores with information on the infrastructure of the communication network. The inputs are regional evaluation scores and network equipment data such as base station information. Specifically, GIS data is used to compare this data and evaluate the communication service quality for each region. The output is a communication quality report for each area.

[0632] Step 4:

[0633] The server sends promotional information to mobile devices only if there is adequate network coverage in a highly-rated area. The input is the quality report and promotional information obtained in step 3. Specifically, the server delivers advertisements and coupons to the device using push notifications. The output is the promotional message displayed on the user's device.

[0634] Step 5:

[0635] The server generates improvement suggestion reports for areas with a high rating of insufficient network coverage. Inputs include communication quality reports and analyzed user behavior data. Specifically, it considers improvement measures and creates a report for feedback to the communication infrastructure department. The output is the improvement suggestion report.

[0636] (Application Example 1)

[0637] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0638] In cities and tourist destinations, there is a need to maximize the appeal of the region and improve user satisfaction. Furthermore, communication service providers need information to understand the communication quality of the region and provide appropriate services. However, until now, there has been a lack of means to comprehensively analyze detailed regional evaluation information and the state of communication infrastructure to provide effective information and services to users.

[0639] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0640] In this invention, the server includes means for acquiring information about areas where users gather, means for analyzing the acquired information and quantifying the evaluation of the area, and means for comparing the evaluation of the area with the basic equipment information of the communication service provider. This makes it possible to effectively transmit promotional information according to the communication coverage status based on the evaluation information of the area, and to generate improvement suggestions based on feedback from users.

[0641] "Users" refer to individuals or groups who utilize this system and are the recipients of relevant information and services within a specific geographical area.

[0642] A "region" refers to a specific geographical area, such as a tourist destination or a city, where people gather and engage in activities.

[0643] "Means of acquiring information" refers to the processes and techniques for collecting relevant information using online data sources such as social media and review sites.

[0644] "Basic equipment information" refers to data related to the infrastructure of the communication network used by communication service providers, including the location of base stations and frequency bands.

[0645] "Means of transmitting promotional information" refers to communication methods and technologies for delivering appropriate promotional information to users' mobile communication devices.

[0646] "Means for generating improvement proposals" refers to systems and methods for analyzing regional evaluation information and user feedback to automatically create improvement measures and various proposals for communication coverage.

[0647] "Evaluation information" refers to evaluations obtained by quantifying or qualitatively analyzing user opinions such as word-of-mouth and reviews regarding a specific region.

[0648] A "mobile communication device" refers to a portable communication device, such as a smartphone or tablet, that can communicate even while on the move.

[0649] The system for realizing this invention is composed of three main components: a server, a terminal, and a user. The server acquires local data online from social media and review sites. Specifically, it collects word-of-mouth and rating information via AP and stores it in a database. The acquired information is analyzed using natural language processing technology on the server (for example, Python's NLTK library). As a result, the rating of a particular region is quantified.

[0650] The server then compares the analysis results with the basic equipment information held by the communication service provider. This basic equipment information includes data on base station locations and frequency bands. This comparison allows for an evaluation of the communication quality in the area. If a suitable communication service is provided in an area with a high evaluation, the server transmits promotional information to the terminal. This promotional information includes data communication discount coupons and advertising messages. The terminal receives this information and notifies the user.

[0651] On the other hand, in areas with high ratings but insufficient communication coverage, the server generates improvement suggestions. These suggestions are sent to the communications infrastructure department as a report highlighting the area's value. This report includes the results of the area's evaluation and user flow pattern analysis, and, like a lubricant, indicates potential improvements to communications services.

[0652] For example, users in urban areas can receive map information for their area and coupons for related tourist attractions on their smartphones while traveling. They can also automatically receive discount information for shopping areas they frequently visit.

[0653] An example of a prompt sentence for a generative AI model is, "Please tell me about popular areas in a specific city and highly-rated tourist attractions associated with those areas."

[0654] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0655] Step 1:

[0656] The server retrieves local reviews and ratings from online data sources (such as APIs). This process automatically collects data from social media and review sites. Inputs include URLs and API keys, while output is raw text data. The server receives this data and stores it in a database.

[0657] Step 2:

[0658] The server analyzes the collected text data using natural language processing (NLP) techniques. Specifically, it performs text summarization and keyword extraction. The input to this process is the raw text data from step 1, and the output is quantified evaluation data. Using NLTK or other NLP libraries, sentiment analysis of the text is performed to quantify the reputation of the area.

[0659] Step 3:

[0660] The server compares the analyzed evaluation data with communication infrastructure equipment information. This process uses base station location data and frequency band data as input. The output is a communication quality evaluation for each region. The server evaluates communication coverage for each region and determines whether there are any deficiencies.

[0661] Step 4:

[0662] The server sends promotional information to terminals in areas with good communication quality. The input consists of evaluation data and promotional content obtained in step 3, while the output is coupons and messages sent to user terminals. The server generates promotional data and sends it to terminals via the distribution system.

[0663] Step 5:

[0664] The server generates a report indicating areas with insufficient communication coverage that require improvement. The input is the communication evaluation data and user behavior data from step 3, and the output is an improvement suggestion report. The server creates the report and provides feedback via a protocol to the communication infrastructure department.

[0665] Step 6:

[0666] The device notifies the user based on promotional information received from the server. The input is promotional information from the server, and the output is a notification message displayed on the user's screen. The device displays the notification in a pop-up format to attract the user's attention.

[0667] Step 7:

[0668] Users check the display on their device and use promotions as needed. Input is notification messages from the device, and output is user actions such as coupon redemption. When users use promotions at specific shops or services, they can provide feedback through the application.

[0669] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0670] As an embodiment of the present invention, a system is constructed with a server at its core and incorporating an emotion engine that recognizes user emotions. The system collects information on geographical areas where users gather and analyzes it using the emotion engine to reflect the emotional data in the evaluation of the area. Through this emotion analysis, the server quantifies the evaluation of the area and compares it with the infrastructure information of the telecommunications carrier to deliver optimal communication services and promotional information.

[0671] Specifically, the server uses its emotion engine to recognize emotional patterns in text and audio data based on the collected information, and analyzes the convenience and popularity of the area. For example, if there are many positive reviews related to a tourist destination, and these reviews contain many emotions such as "fun" and "satisfied," the server will assign a high numerical rating to that area.

[0672] To deliver promotional information based on users' emotional patterns in highly-rated areas, the server optimizes the content of promotions based on emotional data. For example, users with a specific emotional pattern can be offered music or video content that matches their emotions as a coupon.

[0673] Furthermore, if a server has insufficient coverage in a highly-rated area, sentiment data will be taken into account in the maintenance proposal report. Maintenance proposals will also incorporate elements and requests that users perceive positively, and plans will be made to improve the communication infrastructure. This report will more accurately reflect user needs through sentiment recognition, increasing its value in actual maintenance decisions.

[0674] In this way, by improving network services and optimizing promotions while taking user emotions into consideration, we provide a system that enhances the user experience and contributes to the sustainable value creation of telecommunications carriers.

[0675] The following describes the processing flow.

[0676] Step 1:

[0677] The server collects information about geographical areas from online data sources. Specifically, the server retrieves posts and comments related to a particular area through social media APIs. It also collects word-of-mouth information about an area from review sites and stores it in a database.

[0678] Step 2:

[0679] The server analyzes the data collected using an emotion engine to recognize the user's emotional patterns. Specifically, the server uses natural language processing algorithms to extract emotional expressions from the text. This allows it to calculate emotional scores such as positive, negative, and neutral.

[0680] Step 3:

[0681] The server quantifies the area's evaluation based on sentiment scores. Specifically, it calculates the average of the sentiment scores and records it as the area's evaluation. This evaluation can be compared with other area information as a quantified indicator.

[0682] Step 4:

[0683] The server compares area assessments with the telecommunications carrier's infrastructure information. Specifically, it uses equipment data to verify whether existing network coverage is adequately provided in areas with high assessments.

[0684] Step 5:

[0685] Based on the matching results, the server delivers promotional information optimized for mobile devices within the area. For example, it sends content and offers that are particularly appealing to users who exhibit positive emotions. This is received as a notification on the user's mobile device.

[0686] Step 6:

[0687] The server generates reports that utilize sentiment data to propose improvements for high-rated areas with insufficient coverage. Specifically, the reports reflect the emotional experiences and communication service improvement needs that users desire. These reports are submitted to relevant departments within the company to support decision-making regarding network improvements.

[0688] (Example 2)

[0689] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0690] Traditional methods of providing communication services and promotions have failed to adequately optimize services while considering user emotions, making it difficult to improve the user experience. Furthermore, in the development of regional communication infrastructure, it has been impossible to formulate improvement plans that reflect actual user needs and emotions, resulting in inefficient infrastructure development.

[0691] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0692] In this invention, the server includes means for collecting information about areas where users gather, means for performing sentiment analysis on the collected information using a generating AI model and quantifying the evaluation of the area, and means for delivering promotional information optimized based on sentiment patterns to mobile terminals in the relevant area. This makes it possible to provide services that take users' emotions into consideration, and enables the optimization of promotions and the effective planning of communication infrastructure.

[0693] A "user" is an individual or group that utilizes an information system.

[0694] "Region" refers to a specific geographical area, and the scope within which user information related to that area is collected.

[0695] "Information" refers to data collected from users, including text, audio, location data, and social media posts.

[0696] A "generative AI model" is an algorithm or program that uses artificial intelligence to analyze data and recognize user emotions and other patterns.

[0697] "Emotional analysis" is the process of identifying emotional patterns from collected information and tagging them as positive or negative emotions.

[0698] "Quantification" is the process of converting extractive or analytical data into a quantitative format, thereby facilitating comparison and evaluation.

[0699] A "mobile device" is an electronic device that an individual can carry and connect to a communication network.

[0700] "Promotional information" refers to advertisements and offers provided based on specific areas or user emotional patterns, designed to encourage the use of a service.

[0701] "Emotional patterns" refer to a set of emotional tendencies and characteristics that can be recognized from a user's posts and actions.

[0702] "Communication infrastructure" is a general term for the hardware and software that constitute the equipment and foundations that enable voice and data communication.

[0703] This invention provides a system that performs regional evaluation and promotional optimization by collecting and analyzing user emotions. The server, terminal, and user each play crucial roles in the implementation of this system.

[0704] The server is the core component that centrally collects and processes information within a geographical area. The server has an interface for collecting user-generated content, including text and audio data, and performs sentiment analysis on this content using a generative AI model. Sentiment analysis utilizes natural language processing algorithms and speech recognition technology. Specific software components include a sentiment analysis engine and a database management system. Based on the analysis results, the server quantifies the evaluation of a region. For example, tourist destinations with many positive emotions such as "fun" and "satisfied" receive higher ratings.

[0705] The terminal functions as a device for user interaction. User location information and posted data are sent to the server via the terminal, and sentiment analysis is performed in real time. This data is also used to optimize promotional information, delivering content that matches the user's emotional patterns. For example, a user who wants to relax might be offered a coupon for relaxation music.

[0706] Users are the entities that contribute data to the system through their devices by posting emotionally expressive content on social media and other platforms. This user behavioral data can be used to quantify positive impacts in specific regions and inform the development of communication infrastructure and promotional strategies.

[0707] For example, if user posts about a tourist destination contain many words like "fun" and "amazing," it can raise the region's rating and strengthen the promotion of travel packages. A simple example of a prompt for a generative AI model would be text such as, "Analyze the positive reviews about this area and quantify its popularity based on that content."

[0708] The system provided by this embodiment enables service improvements that take user emotions into consideration, facilitates efficient promotion by telecommunications carriers, and facilitates sustainable value creation.

[0709] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0710] Step 1:

[0711] Users take photos in their daily lives and at places they visit, and post comments and reviews on social media. This allows users to generate information about geographical areas and provide it in a digitized format. In this step, data including the user's location and emotions is generated as input.

[0712] Step 2:

[0713] The device collects user-generated data and sends it to the server. This process includes location information and text data. The input for this step is raw data provided by the user, and the output is data converted to a format suitable for the server. Pre-filtering necessary for sentiment analysis may also be performed.

[0714] Step 3:

[0715] The server receives data sent from the terminal. Using a generative AI model, it analyzes emotions from text and audio. This analysis includes recognizing emotional patterns using natural language processing techniques and tagging positive and negative emotions. The input is data received from the terminal, and the output is analyzed emotional data.

[0716] Step 4:

[0717] The server evaluates geographical areas based on the results of sentiment analysis and quantifies that evaluation. For example, if a tourist destination is filled with positive comments, its evaluation score will be high. In this step, sentiment analysis data is the input, and a multidimensional evaluation score is the output. This evaluation serves as an indicator of the convenience and popularity of the region.

[0718] Step 5:

[0719] The server matches quantified area evaluations with infrastructure information from telecommunications carriers to design optimal promotional information. It generates coupons for music and video content of interest to users with specific emotional patterns. In this step, area evaluations and communication infrastructure data are input, and an emotionally adaptive promotional strategy is output.

[0720] Step 6:

[0721] The server generates a report proposing improvements to communication infrastructure if coverage is potentially lacking in highly-rated areas. By incorporating user sentiment data, the improvement proposals become more realistic and effective. Inputs are area ratings and sentiment data, and the output is a direct improvement proposal report.

[0722] Through this processing step, the system gains the ability to accurately understand the user's emotions and provide optimal network services and promotional information.

[0723] (Application Example 2)

[0724] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0725] In smart cities, there is a lack of means to help residents and visitors accurately understand the convenience and popularity of different areas within the city and choose the best places to spend their time. Furthermore, there is a need to improve the overall user experience of the city through the optimization of communication infrastructure and the provision of real-time information to residents.

[0726] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0727] In this invention, the server includes a device for collecting information about the geographical area where users gather, a device for analyzing the collected information and quantifying the evaluation of the area, and a device for providing sentiment analysis data about the area surrounding the user in real time. As a result, residents of a smart city can obtain real-time evaluation information about the area, thereby improving the user experience of the city.

[0728] A "user" is an individual or group that uses the system.

[0729] A "geographical area" is a specific physical area where information is collected and evaluated.

[0730] "Information-collecting devices" refer to hardware or software used to acquire data related to geographical areas.

[0731] A "device for analyzing information and quantifying evaluations" is a system for analyzing collected information and performing quantitative evaluations.

[0732] A "communications provider" is a company or business that provides communication services.

[0733] A "device for distributing sales promotion information" is a system that transmits the content of advertisements and promotions to users within the relevant area.

[0734] A "device that outputs proposals regarding maintenance" is a system for presenting areas for improvement and construction plans within a geographical area.

[0735] "Sentiment analysis data" refers to the results of analyzing emotions from user feedback and comments.

[0736] A "device that provides information in real time" is a platform for instantly transmitting the latest information to users.

[0737] A "mobile terminal" is a device with communication capabilities that a user can carry with them.

[0738] A "report generation device" is a system that compiles analysis results and evaluation information into a document.

[0739] To implement this invention, the server needs to be equipped with a device that collects and analyzes information about users' emotions and movements within a geographical area. Users receive emotion data about the area in real time using smartphones or other mobile devices. This system is built using programming languages ​​such as Python or Node.js, and employs natural language processing libraries such as TensorFlow or PyTorch for emotion analysis. Based on these analysis results, the server presents appropriate sales promotion information and area evaluations to residents and visitors.

[0740] For example, if a tourist destination receives a large amount of positive feedback, the server can rate that area highly and offer special events or discounts to tourists. This allows tourists to choose places they will enjoy more and make the most of their visit. An example of a prompt the server might use in this process is, "Please tell me the latest sentiment trends in this area."

[0741] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0742] Step 1:

[0743] The server collects user movement and sentiment data from geographical areas. Inputs include location information and text data obtained from smartphones and various sensors. The server stores the received data in a database and prepares it for analysis.

[0744] Step 2:

[0745] The server inputs the collected data into the sentiment analysis engine and assigns sentiment labels. Sentiment analysis uses TensorFlow to perform natural language processing on the data, associating sentiment values ​​such as positive, negative, and neutral with each text data point. The output is the sentiment label associated with each data point.

[0746] Step 3:

[0747] The server quantifies sentiment labels and aggregates them by geographical region. It averages or aggregates the input sentiment data across each region and generates a region evaluation score based on this. This process uses a Python data aggregation script. The output is the evaluation score for each region.

[0748] Step 4:

[0749] The server determines relevant sales promotion information for each area based on the evaluation score. For areas with high evaluation scores, it selects positive promotional campaigns; for areas with low scores, it selects information including improvement suggestions. The selected information is then entered into the sales promotion campaign service within the server.

[0750] Step 5:

[0751] The terminal displays evaluation scores and sales promotion information received from the server in real time to the user. The terminal uses GPS functionality to determine the user's current location and displays information about the corresponding area on the user interface. This allows the user to visually check the area's evaluation and related event information.

[0752] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the controlled object 443 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0753] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0754] 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 this disclosure is not limited thereto, and the specific processing may also be performed by the robot 414.

[0755] Furthermore, the emotion identification model 59, acting as an emotion engine, may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to a specific mapping, which is an emotion map (see Figure 9). Similarly, the emotion identification model 59 may also determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[0756] Figure 9 shows an emotion map 400 in which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. The closer to the center of the concentric circles, the more primitive the emotions are located. Further out of the concentric circles, emotions representing states and actions arising from mental states are located. Emotion is a concept that includes feelings and mental states. On the left side of the concentric circles, emotions that are generally generated from reactions occurring in the brain are located. On the right side of the concentric circles, emotions that are generally induced by situational judgment are located. Above and below the concentric circles, emotions that are generally generated from reactions occurring in the brain and induced by situational judgment are located. In addition, the emotion of "pleasure" is located on the upper side of the concentric circles, and the emotion of "displeasure" is located on the lower side. Thus, in the emotion map 400, multiple emotions are mapped based on the structure in which emotions arise, and emotions that are likely to occur simultaneously are mapped close together.

[0757] These emotions are distributed at the 3 o'clock position on the Emotion Map 400, and usually fluctuate between feelings of security and anxiety. In the right half of the Emotion Map 400, situational awareness takes precedence over internal feelings, resulting in a calm impression.

[0758] The inside of the Emotion Map 400 represents inner thoughts, while the outside represents actions. Therefore, the further you go from the outside of the Emotion Map 400, the more visible (expressed in actions) your emotions become.

[0759] Here, human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. Similarly, in robots, cars, motorcycles, etc., emotions can be created based on various balances, such as posture and battery level. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. The emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on a system for analyzing brain physiological signals of speech emotion recognition and emotion, Tokushima University, doctoral dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map contains emotions belonging to a region called "response," where sensation is dominant. The right half of the emotion map contains emotions belonging to a region called "situation," where situational awareness is dominant.

[0760] The emotion map defines two emotions that promote learning. One is the emotion around the middle of the negative "repentance" and "reflection" on the situation side. In other words, it is when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is the emotion around the positive "desire" on the reaction side. In other words, it is when the robot has positive feelings such as "I want more" or "I want to know more."

[0761] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​representing each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple training data sets, which are combinations of user input and emotion values ​​representing each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions located close together have similar values, as shown in the emotion map 900 in Figure 10. Figure 10 shows an example where multiple emotions such as "reassured," "calm," and "confident" have similar emotion values.

[0762] The above description primarily focuses on the functions of the data processing device 12 in relation to this disclosure. However, the system related to this disclosure is not necessarily implemented on a server. The system related to this disclosure may be implemented as a general information processing system. This disclosure may be implemented, for example, as a software program that runs on a personal computer or as an application that runs on a smartphone. The method related to this disclosure may be provided to users in SaaS (Software as a Service) format.

[0763] In the above embodiment, an example was given in which a specific process is performed by a single computer 22. However, the technology of this disclosure is not limited thereto, and a distributed processing of the specific process may be performed by multiple computers, including computer 22. For example, a data generation model 58 may be provided in an external device of the data processing device 12, and the external device may generate data according to the input data.

[0764] In the above embodiment, an example was given in which the specific processing program 56 is stored in the storage 32, but the technology of this disclosure is not limited thereto. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-temporary storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-temporary storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes specific processing according to the specific processing program 56.

[0765] Alternatively, the specific processing program 56 may be stored in a storage device such as a server connected to the data processing device 12 via the network 54, and the specific processing program 56 may be downloaded and installed on the computer 22 in response to a request from the data processing device 12.

[0766] Furthermore, it is not necessary to store the entirety of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store the entirety of the specific processing program 56 in the storage 32; it is acceptable to store only a portion of the specific processing program 56.

[0767] The following types of processors can be used as hardware resources to perform specific processing. Examples of processors include a CPU, a general-purpose processor that functions as a hardware resource to perform specific processing by executing software, i.e., a program. Other examples of processors include dedicated electrical circuits, such as FPGAs (Field-Programmable Gate Arrays), PLDs (Programmable Logic Devices), or ASICs (Application Specific Integrated Circuits), which have circuit configurations specifically designed to perform specific processing. All of these processors have built-in or connected memory, and all of them perform specific processing by using memory.

[0768] The hardware resource that performs a specific process may consist of one of these various processors, or it may consist of a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Alternatively, the hardware resource that performs a specific process may consist of a single processor.

[0769] Examples of configurations using a single processor include, firstly, a configuration in which one or more CPUs and software are combined to form a single processor, and this processor functions as a hardware resource that performs a specific process. Secondly, there is a configuration using a processor that realizes the functions of the entire system, including multiple hardware resources that perform a specific process, on a single IC chip, as exemplified by SoCs (System-on-a-chip). In this way, a specific process is realized using one or more of the above types of processors as hardware resources.

[0770] Furthermore, the hardware structure of these various processors can more specifically utilize electrical circuits that combine circuit elements such as semiconductor devices. Also, the specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps can be deleted, new steps added, or the processing order rearranged, as long as it does not deviate from the main purpose.

[0771] The descriptions and illustrations presented above are detailed explanations of the technical aspects of this disclosure and are merely examples of the technical aspects. For example, the above descriptions of the structure, function, operation, and effect are examples of the structure, function, operation, and effect of the technical aspects of this disclosure. Therefore, it goes without saying that you may delete unnecessary parts, add new elements, or replace elements in the descriptions and illustrations presented above, as long as you do not deviate from the essence of the technical aspects of this disclosure. Furthermore, in order to avoid confusion and facilitate understanding of the technical aspects of this disclosure, explanations of common technical knowledge and the like that do not require special explanation to enable the implementation of the technical aspects of this disclosure have been omitted from the descriptions and illustrations presented above.

[0772] All documents, patent applications, and technical standards described herein are incorporated by reference to the same extent as if each individual document, patent application, and technical standard were specifically and individually noted to be incorporated by reference.

[0773] The following is further disclosed regarding the embodiments described above.

[0774] (Claim 1)

[0775] Means of collecting information about the geographical areas where users gather,

[0776] A means of analyzing the collected information and quantifying the evaluation of the area,

[0777] A means of evaluating geographical areas and matching them with information on the infrastructure facilities of telecommunications carriers,

[0778] A means of delivering promotional information to mobile devices within the relevant area,

[0779] A system including a means for outputting proposals regarding the development of the area in question.

[0780] (Claim 2)

[0781] The system according to claim 1, further comprising means for analyzing human flow data within a geographical area and reflecting it in the evaluation of the area.

[0782] (Claim 3)

[0783] The system according to claim 1, further comprising means for generating a report for making maintenance suggestions when coverage is insufficient in the area in question.

[0784] "Example 1"

[0785] (Claim 1)

[0786] A means of collecting data about the areas where users gather,

[0787] A method for quantifying the evaluation of a region using natural language processing technology, utilizing the collected data,

[0788] A means of comparing regional evaluation information with network equipment data of telecommunications companies,

[0789] A means of transmitting advertising information to mobile devices within an area,

[0790] A system including means for generating proposals for improving the communication environment in a region.

[0791] (Claim 2)

[0792] The system according to claim 1, further comprising means for analyzing user behavior data within a region and integrating it into an evaluation.

[0793] (Claim 3)

[0794] The system according to claim 1, further comprising means for generating a report indicating suggestions for improvement when network coverage in the relevant area is insufficient.

[0795] "Application Example 1"

[0796] (Claim 1)

[0797] Means of obtaining information about areas where users gather,

[0798] A means of analyzing acquired information and quantifying the evaluation of the region,

[0799] A means of comparing regional assessments with basic equipment information of telecommunications service providers,

[0800] A means of transmitting promotional information to mobile communication devices within the relevant area,

[0801] A means of presenting proposals for improvement in the area in question,

[0802] A means for displaying regional evaluation information on a mobile communication device,

[0803] A system that includes means for generating improvement suggestions based on user feedback.

[0804] (Claim 2)

[0805] The system according to claim 1, further comprising means for analyzing human movement data within a region and reflecting it in the evaluation of the region.

[0806] (Claim 3)

[0807] The system according to claim 1, further comprising means for generating a report for suggesting improvements when communication coverage is insufficient in the area in question.

[0808] "Example 2 of combining an emotion engine"

[0809] (Claim 1)

[0810] Means of collecting information about the areas where users gather,

[0811] A method for quantifying the evaluation of a region by analyzing the sentiment of collected information using a generative AI model,

[0812] A means of comparing regional assessments with information on the infrastructure facilities of telecommunications carriers,

[0813] A means of delivering promotional information optimized based on emotional patterns to mobile devices within the relevant region,

[0814] A system that includes a means for outputting development proposals for highly-rated areas, taking sentiment data into consideration.

[0815] (Claim 2)

[0816] The system according to claim 1, further comprising means for analyzing information on the flow of people within a geographical area and influencing the evaluation of the region.

[0817] (Claim 3)

[0818] The system according to claim 1, further comprising means for generating a report based on sentiment data for making improvement proposals when coverage is insufficient in the area in question.

[0819] "Application example 2 when combining with an emotional engine"

[0820] (Claim 1)

[0821] A device that collects information about the geographical area where users gather,

[0822] A device that analyzes collected information and quantifies the evaluation of the area,

[0823] A device for evaluating geographical areas and matching them with information on the infrastructure facilities of telecommunications providers,

[0824] A device that distributes sales promotion information to mobile terminals within the relevant area,

[0825] A device that outputs proposals regarding the development of the relevant area,

[0826] A device that provides real-time sentiment analysis data about the area surrounding the user,

[0827] A device that presents convenience information based on evaluation data of the domain,

[0828] A system that includes this.

[0829] (Claim 2)

[0830] The system according to claim 1, further comprising a device for analyzing individual movement data within a geographical area and reflecting the results in an evaluation of the area.

[0831] (Claim 3)

[0832] The system according to claim 1, further comprising a device for generating a report for making maintenance suggestions when communication coverage is insufficient in the relevant area. [Explanation of symbols]

[0833] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Devices 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robots< / url:> < / url:> < / url:> < / url:>

Claims

1. Means of collecting information about the geographical areas where users gather, A means of analyzing the collected information and quantifying the evaluation of the area, A means of evaluating geographical areas and matching them with information on the infrastructure facilities of telecommunications carriers, A means of delivering promotional information to mobile devices within the relevant area, A system including a means for outputting proposals regarding the development of the area in question.

2. The system according to claim 1, further comprising means for analyzing human flow data within a geographical area and reflecting it in the evaluation of the area.

3. The system according to claim 1, further comprising means for generating a report for making maintenance suggestions when coverage is insufficient in the area in question.

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