Methods for evaluating and operating franchises and their electronic devices

Abstract

The present invention relates to a method for evaluating and operating a franchise store and an electronic device thereof.

Description

Technology Field

[0001] The present invention relates to a method for evaluating and operating a franchise store and an electronic device thereof.

[0002] delete Background Technology

[0003] Unless otherwise indicated in this specification, the contents described in this section are not prior art for the claims of this application, and are not to be recognized as prior art simply because they are included in this section.

[0004] One of the key aspects of operating a franchise is the management of the franchisees. Monitoring the current operational status of the stores and providing corresponding feedback to ensure smooth business operations is a mutually beneficial approach for both the franchisees and the franchisor.

[0005] Accordingly, the present invention proposes a technology that evaluates franchise stores and provides feedback based on the evaluation, thereby enabling the smooth operation of franchise stores.

[0006] delete Prior art literature

[0007] Korean Registered Patent No. 10-1979892 (May 13, 2019) The problem to be solved

[0008] One embodiment of the present invention provides an apparatus and method for providing a service for monitoring and evaluating the operational status of a franchise store.

[0009] The technical problems to be solved by the present invention are not limited to those mentioned above, and other technical problems not mentioned will be clearly understood by those skilled in the art to which the present invention belongs from the description below.

[0010] delete means of solving the problem

[0011] To achieve the above-mentioned purpose, an electronic device according to one embodiment of the present invention includes a memory and a processor connected to the memory, wherein the processor receives first operational information and first consultation information regarding a first franchisee from a first franchisee terminal, derives a first franchisee evaluation score regarding the first franchisee based on the first operational information and the first consultation information, generates operational feedback information regarding the first franchisee based on the first franchisee evaluation score, and transmits the operational feedback information to the first franchisee terminal.

[0012] At this time, the first operational information includes, for the first franchisee, first location information, sales information by a pre-set target period, operating profit information, and franchisee product order quantity, and the first consultation information may include, for the first franchisee, information regarding consultation details through pre-set consultation media.

[0013] At this time, the processor can derive a sales score regarding the sales performance of the first franchise based on the first operation information, derive an operation score regarding the operation status of the first franchise based on the first consultation information, and derive the first franchise evaluation score based on the sales score and the operation score.

[0014] At this time, the processor may, based on the first location information, extract a region corresponding to the first location information from among regions divided into preset sections as a target region, and extract a franchisee located in the target region as a second franchisee (including the first franchisee).

[0015] At this time, the above sales score is derived by the following mathematical formula,

[0016]

[0017] SS(Sales Score) refers to the above sales score, a_1 refers to the average sales amount of the above second franchise stores during the above target period, a_2 refers to the average sales amount of the above first franchise store during the above target period, b_1 refers to the average operating profit of the above second franchise stores during the above target period, b_2 refers to the average operating profit of the above first franchise store during the above target period, c_1 refers to the average franchise product order amount of the above second franchise stores during the above target period, and c_2 refers to the average franchise product order amount of the above first franchise store during the above target period.

[0018] At this time, the processor converts multiple consultation records by consultation medium into text information, tokenizes the text information by each keyword, calculates TF-IDF weights for each tokenized keyword, extracts keywords extracted in order of highest TF-IDF weights up to a predetermined threshold number as a representative keyword group for the consultation records, derives a positive or negative evaluation for the consultation records based on the representative keyword group through a Large Language Model (LM) module trained to determine whether the keywords have a positive or negative meaning, and derives the operation score for the first franchise based on the positive or negative evaluation for all consultation records.

[0019] At this time, the above operating score is derived by the following mathematical formula,

[0020]

[0021] OS (Operating Score) refers to the above operating score, d_1 refers to the total number of consultation records for the above first franchisee, d_2 refers to the number of consultation records corresponding to positive evaluations for the above first franchisee, e_1 refers to the average of the total number of consultation records for the above second franchisees, and e_2 refers to the average of the number of consultation records corresponding to positive evaluations for the above second franchisees.

[0022] At this time, the above-mentioned first franchise evaluation score is derived by the following mathematical formula,

[0023]

[0024] 1ES (Evaluation Score) may mean the first franchise evaluation score, SS may mean the sales score, and OS may mean the operation score.

[0025] At this time, the processor, when the first franchise evaluation score is less than or equal to a preset threshold evaluation score, compares the sales score and the operation score corresponding to the first franchise evaluation score with the preset threshold sales score and threshold operation score, respectively; when the sales score is less than or equal to the threshold sales score and the operation score is less than or equal to the threshold operation score, derives a preset number of recommended franchise items in order of highest sales among franchise items based on the sales information of the second franchise stores, generates recommended franchise item information, generates operation feedback information including the recommended franchise item information and indicating that courtesy consultation training is required, when the sales score is less than or equal to the threshold sales score and the operation score exceeds the threshold operation score, generates operation feedback information including the recommended franchise item information, when the sales score exceeds the threshold sales score and the operation score is less than or equal to the threshold operation score, generates operation feedback information indicating that courtesy consultation training is required, and when the sales score is the If the threshold sales score is exceeded and the above operation score exceeds the above threshold operation score, the above operation feedback information indicating that the operation of the above first franchise store is excellent can be generated.

[0026] At this time, when the processor receives a request for a recommendation for a new establishment area from an administrator terminal, it may derive a new establishment score for each region divided into pre-configured sections, generate recommendation information recommending the region with the highest new establishment score as the new establishment area, and transmit it to the administrator terminal.

[0027] At this time, the processor can derive the new establishment score for each region based on the number of third franchise stores installed in each region and the second franchise evaluation scores of the third franchise stores.

[0028] At this time, the above new establishment score is derived by the following mathematical formula,

[0029]

[0030] NES (New Establichment Score) refers to the new establishment score of the region, f refers to the average of the second franchise evaluation scores of the third franchise stores located in the region, and g may refer to the number of the third franchise stores located in the region.

[0031] In addition, a method for providing a service for monitoring and evaluating the operational status of a franchisee may include the steps of receiving first operational information and first consultation information regarding a first franchisee from a first franchisee terminal, deriving a first franchisee evaluation score regarding the first franchisee based on the first operational information and the first consultation information, generating operational feedback information regarding the first franchisee based on the first franchisee evaluation score, and transmitting the operational feedback information to the first franchisee terminal.

[0032] In addition, it may be implemented as a computer program stored on a computer-readable recording medium to execute a method for providing monitoring and evaluation services of the operational status of franchisees in combination with hardware.

[0033] In addition, the method of providing a service for monitoring and evaluating the operational status of a franchisee, combined with hardware, can be implemented using a computer-readable recording medium storing a computer program.

[0034] delete

[0035] The effects obtainable from the present invention are not limited to those mentioned above, and other unmentioned effects will be clearly understood by those skilled in the art from the description below.

[0036] delete Effects of the invention

[0037] As such, according to one embodiment of the present invention, a device and method for providing a service for monitoring and evaluating the operational status of a franchise store can be provided.

[0038] The effects obtainable from the present invention are not limited to those mentioned above, and other unmentioned effects will be clearly understood by those skilled in the art from the description below.

[0039] delete Brief explanation of the drawing

[0040] Other aspects, features, and benefits of specific preferred embodiments of the present invention, as described above, will become more apparent from the following description in conjunction with the accompanying drawings. FIG. 1 is a diagram showing the configuration of an electronic device according to one embodiment. FIG. 2 is a diagram showing the configuration of a program according to one embodiment. FIG. 3 is a conceptual diagram of a device for providing monitoring and evaluation services for the operational status of a franchise store according to one embodiment. FIG. 4 is a block diagram of an electronic device according to one embodiment. FIG. 5 is a diagram showing the derivation of a first franchise evaluation score according to one embodiment. FIG. 6 is a drawing showing a first franchise store and a second franchise store according to one embodiment. FIG. 7 is a diagram showing the derivation of a representative keyword group according to one embodiment. FIG. 8 is a diagram showing how positive or negative evaluations are determined for each consultation record through LLM according to one embodiment. FIGS. 9 and FIGS. 10 are drawings showing the derivation of new establishment scores by region according to one embodiment. FIG. 11 is a flowchart of a method for providing a service for monitoring and evaluating the operational status of a franchise store according to one embodiment. It should be noted that in the drawings above, similar reference numbers are used to illustrate identical or similar elements, features, and structures. Specific details for implementing the invention

[0041] The following embodiments are combinations of the components and features of the embodiments in a predetermined form. Each component or feature may be considered optional unless otherwise explicitly stated. Each component or feature may be implemented in a form not combined with other components or features. Additionally, various embodiments may be constructed by combining some components and / or features. The order of operations described in various embodiments may be changed. Some components or features of one embodiment may be included in another embodiment, or may be replaced with corresponding components or features of another embodiment.

[0042] In the description of the drawings, procedures or steps that could obscure the essence of the various embodiments were not described, nor were procedures or steps that can be understood by a person of ordinary knowledge in the relevant technical field described.

[0043] Throughout the specification, when a part is described as "comprising" or "including" a component, this means that, unless specifically stated otherwise, it does not exclude other components but may include additional components. Furthermore, terms such as "...part," "...unit," and "module" as used in the specification refer to a unit that performs at least one function or operation, and this may be implemented in hardware, software, or a combination of hardware and software. Additionally, "one (a or an)," "one," "the," and similar related terms may be used in the context describing various embodiments (particularly in the context of the following claims) in both singular and plural forms, unless otherwise indicated in the specification or clearly contradicted by the context.

[0044] Hereinafter, embodiments according to various examples will be described in detail with reference to the accompanying drawings. The detailed description disclosed below, together with the accompanying drawings, is intended to describe exemplary embodiments of various examples and is not intended to represent the only embodiment.

[0045] In addition, specific terms used in various embodiments are provided to aid in understanding the various embodiments, and the use of such specific terms may be modified in other forms within the scope of not departing from the technical concept of the various embodiments.

[0046] delete

[0047] FIG. 1 is a diagram showing the configuration of an electronic device according to one embodiment, and FIG. 2 is a diagram showing the configuration of a program according to one embodiment.

[0048] The configuration of the electronic device and program for Figures 1 and 2 will be described in more detail later.

[0049] delete

[0050] Referring to FIG. 3, a device (101) providing a monitoring and evaluation service for the operational status of a franchise store according to one embodiment of the present invention evaluates the franchise store based on the sales status and operational status of the franchise store, and based on the evaluation results, transmits feedback to the first franchise store terminal containing information necessary for the franchise store, thereby enabling smooth operation. In the case of establishing a new franchise store, it may derive a region favorable for new establishment by region and transmit it to a manager terminal.

[0051] At this time, the first merchant terminal (300) and the manager terminal may include a desktop computer, laptop computer, notebook, smartphone, tablet PC, mobile phone, smart watch, smart glass, e-book reader, PMP (portable multimedia player), portable game console, navigation device, digital camera, DMB (digital multimedia broadcasting) player, digital audio recorder, digital audio player, digital video recorder, digital video player, PDA (Personal Digital Assistant), etc.

[0052] delete

[0053] FIG. 4 is a block diagram of an electronic device (101) according to one embodiment of the present invention.

[0054] Referring to FIG. 4, a device (101) providing an operating status monitoring and evaluation service for a franchise store according to one embodiment of the present invention may include a memory and a processor connected to the memory.

[0055] At this time, the processor (120) can receive first operation information and first consultation information regarding the first merchant from the first merchant terminal.

[0056] At this time, the first operational information may include first location information, sales information by a pre-set target period, operating profit information, and franchise product order volume for the first franchise store.

[0057] At this time, the target period may be arbitrarily set by the manager of the present invention, for example, 1 month, 3 months, or 6 months.

[0058] In addition, the first consultation information may include information regarding consultation history through pre-established consultation media for the first franchisee.

[0059] At this time, the consultation medium may include all media through which a customer can conduct a consultation, such as telephone consultation, text consultation, or chatbot consultation, and the consultation details may be recordings, document files, etc., through each consultation medium.

[0060] In addition, the processor (120) can derive a first franchise evaluation score for the first franchise store based on the first operation information and the first consultation information. This will be described in more detail later.

[0061] Additionally, the processor (120) can generate operational feedback information for the first franchise based on the first franchise evaluation score and transmit the operational feedback information to the first franchise terminal.

[0062] Through this, the business operator operating the first franchise store can be enabled to operate more smoothly.

[0063] delete

[0064] FIG. 5 is a diagram showing the derivation of a first franchise evaluation score according to one embodiment.

[0065] Referring to FIG. 5, the processor (120) can derive a sales score regarding sales performance for the first franchise based on the first operation information, derive an operation score regarding the operation status of the first franchise based on the first consultation information, and derive the first franchise evaluation score based on the sales score and the operation score.

[0066] At this time, when deriving the above sales score, in order to determine whether the regional characteristics where the above first franchise store is located affect sales, the sales of other second franchise stores in adjacent regions may also be considered.

[0067] FIG. 6 is a drawing showing a first franchise store and a second franchise store according to one embodiment.

[0068] Referring to FIG. 6, the processor (120) can extract a region corresponding to the first location information from among regions divided into preset sections based on the first location information, and extract a franchisee located in the target region as a second franchisee (including the first franchisee).

[0069] At this time, the above region may be a region divided into sections arbitrarily set by the manager of the present invention, or a region divided into administrative districts such as cities, counties, and districts.

[0070] At this time, the above sales score can be derived by the following mathematical formula 1.

[0071] [Mathematical Formula 1]

[0072]

[0073] At this time, SS (Sales Score) refers to the sales score, a_1 refers to the average sales amount of the second franchise stores during the target period, a_2 refers to the average sales amount of the first franchise store during the target period, b_1 refers to the average operating profit of the second franchise stores during the target period, b_2 refers to the average operating profit of the first franchise store during the target period, c_1 refers to the average franchise product order amount of the second franchise stores during the target period, and c_2 refers to the average franchise product order amount of the first franchise store during the target period.

[0074] Through this, the sales score of the first franchisee can be objectively derived based on the sales and operating profits of adjacent second franchisees.

[0075] However, since the scale of adjacent second franchise stores may differ from the aforementioned first franchise store, the ratio of the franchise product order amount was reflected.

[0076] delete

[0077] FIG. 7 is a diagram showing the derivation of a representative keyword group according to one embodiment.

[0078] Based on the consultation records, it is necessary to determine whether the first franchisee is currently operating courteously or if there are any operational issues.

[0079] Accordingly, referring to FIG. 7, the processor (120) can convert multiple consultation records by consultation medium into text information, tokenize the text information by each keyword, calculate TF-IDF weights for each tokenized keyword, and extract keywords extracted in order of highest TF-IDF weights up to a predetermined threshold number as representative keyword bundles for the consultation records.

[0080] In this case, an example of tokenization would be extracting keywords such as ‘food, salty, staff, unfriendly’ from the above text information, ‘the food is very salty and the staff is unfriendly’.

[0081] At this time, at least one of Soynlp, koNLpy, or a tokenizer can be used as the tokenization module.

[0082] soynlp is a Python package for Korean language processing. While the morphological analyzer provided by koNLPy offers the ability to tokenize documents based on morphemes, it has the disadvantage of not recognizing newly created, unregistered words well. To resolve this, one must go through the process of registering words in a user dictionary. To assist with this process, soynlp provides a function that enables tokenization based on cohesion without a user dictionary or morphological analysis. KoNLPy is a package that allows for Korean language information processing using Python. A tokenizer, like Soynlp and koNLpy, refers to a library that breaks down natural language into words or subwords and converts them into standard words registered in a dictionary.

[0083] In addition, the aforementioned TF-IDF (Term Frequency - Inverse Document Frequency) weight is a weight used in information retrieval and text mining, and is a statistical figure indicating how important a word is within a specific document when there is a group of documents consisting of multiple documents. It can be used for purposes such as extracting keywords from documents, determining the ranking of search results in search engines, or calculating the degree of similarity between documents.

[0084] In this context, TF (term frequency) is a value indicating how often a specific word appears within a document; the higher this value, the more important the word is considered to be in the document. However, if a word itself is used frequently within a document group, it means that the word appears commonly. This is called DF (document frequency), and its reciprocal is called IDF (inverse document frequency). TF-IDF is the product of TF and IDF.

[0085] In this case, the IDF value is determined by the nature of the document group. For example, the word 'atom' does not appear frequently among general documents, so its IDF value is high and it can become a keyword of the document; however, in the case of a document group containing documents about atoms, this word becomes a cliché, and other words that can subdivide and distinguish each document receive a higher weight.

[0086] At this time, if we look at the mathematical explanation of the above TF-IDF weights, as shown in Fig. 3, tf(t,d) represents the frequency of the word t appearing in document d, w represents the total number of words included in document d, and |D| represents the size of the document set D, that is, the number of d included in D.

[0087] Through this, a TF-IDF weight can be calculated for each keyword included in the above character information, and a threshold number of keywords can be extracted as a representative keyword group in order of highest TF-IDF weight.

[0088] At this time, the threshold number can be arbitrarily set by the manager of the present invention, for example, 5, 10, etc.

[0089] delete

[0090] FIG. 8 is a diagram showing how positive or negative evaluations are determined for each consultation record through LLM according to one embodiment.

[0091] Referring to FIG. 8, the processor (120) can derive a positive or negative evaluation for the consultation history based on the representative keyword set through a Large Language Model (LM) module trained to determine whether the keyword has a positive or negative meaning, and derive the operation score for the first franchisee based on the positive or negative evaluation for the entire consultation history.

[0092] At this time, the LLM (Large Language Model) operating in the above LLM module refers to an artificial intelligence system capable of processing a vast amount of natural language data and generating responses that are often indistinguishable from human-generated text. The LLM is built using deep learning technology, is trained on a vast amount of text data such as books, articles, and online content, and can derive responses based on user requests.

[0093] The most well-known LLMs include OpenAI's GPT (Generative Pre-trained Transformer) series and Google's BERT (Bidirectional Encoder Representations from Transformers) models. These models are used in various applications, including language translation, content generation, and chatbots.

[0094] At this time, the above operating score can be derived by the following mathematical formula 2.

[0095] [Mathematical Formula 2]

[0096]

[0097] At this time, OS (Operating Score) refers to the above operating score, d_1 refers to the total number of consultation records for the above first franchisee, d_2 refers to the number of consultation records corresponding to positive evaluations for the above first franchisee, e_1 refers to the average of the total number of consultation records for the above second franchisees, and e_2 refers to the average of the number of consultation records corresponding to positive evaluations for the above second franchisees.

[0098] Based on the sales score and operation score derived as above, the first franchise evaluation score is derived, but to examine it in more detail, the first franchise evaluation score can be derived by the following mathematical formula 3.

[0099] [Mathematical Formula 3]

[0100]

[0101] At this time, 1ES (Evaluation Score) may mean the first franchise evaluation score, SS may mean the sales score, and OS may mean the operation score.

[0102] At this time, the processor (120) can first compare the first franchise evaluation score with a preset threshold evaluation score.

[0103] The above threshold evaluation score can be set as the average of the franchise evaluation scores for all franchisees.

[0104] At this time, if the first franchise evaluation score is less than or equal to the threshold evaluation score, the processor (120) can compare the sales score and the operation score corresponding to the first franchise evaluation score with the preset threshold sales score and threshold operation score, respectively.

[0105] The above threshold sales score can be set as the average of the sales scores for all franchise stores, and the above threshold operation score can be set as the average of the operation scores for all franchise stores.

[0106] At this time, the processor (120) can generate recommended franchise product information by deriving a preset number of recommendations in order of highest sales among franchise products based on the sales information of the second franchise stores when the sales score is less than or equal to the threshold sales score and the operation score is less than or equal to the threshold operation score, and can generate operation feedback information that includes the recommended franchise product information and indicates that friendly consultation training is required.

[0107] At this time, the number of recommendations can be arbitrarily set by the manager of the present invention, for example, to 5 or 10.

[0108] Additionally, the processor (120) can generate the operation feedback information including the recommended franchise product information when the sales score is less than or equal to the threshold sales score and the operation score exceeds the threshold operation score.

[0109] Additionally, the processor (120) can generate operational feedback information indicating that friendly counseling training is required when the sales score exceeds the threshold sales score and the operation score is less than or equal to the threshold operation score.

[0110] Additionally, the processor (120) can generate operation feedback information indicating that the operation of the first franchise is excellent when the sales score exceeds the threshold sales score and the operation score exceeds the threshold operation score.

[0111] Through this, the above sales score and the above operation score can be improved.

[0112] delete

[0113] FIGS. 9 and FIGS. 10 are drawings showing the derivation of new establishment scores by region according to one embodiment.

[0114] The manager of the present invention may determine which region should be established for the new establishment of a franchise. At this time, an indicator is required regarding which region should be established to enable smoother and more efficient operation.

[0115] To this end, the present invention derives new establishment scores by region to assist the manager in selecting a location to establish a new franchise.

[0116] Referring to FIGS. 9 and 10, when the processor (120) receives a request for a new establishment area recommendation from a manager terminal, it can derive a new establishment score for each area divided into pre-set sections, generate recommendation information recommending the area with the highest new establishment score as the new establishment area, and transmit it to the manager terminal.

[0117] At this time, the processor (120) can derive the new establishment score for each region based on the number of third franchise stores installed in each region and the second franchise evaluation score of the third franchise stores.

[0118] In this case, if the second franchise evaluation score of third franchisees located in the area is high, the area may have a geographical advantage for smooth operation, and the above new establishment score can be derived by utilizing the fact that the competitive structure is somewhat unfavorable when there are many third franchisees located in the area.

[0119] Looking at it in more detail, the above new establishment score can be derived by the following mathematical formula 4.

[0120] [Mathematical Formula 4]

[0121]

[0122] In this case, NES (New Establichment Score) refers to the new establishment score of the region, f refers to the average of the second franchise evaluation scores of the third franchise stores located in the region, and g may refer to the number of the third franchise stores located in the region.

[0123] Through this, the most efficient region can be identified.

[0124] delete

[0125] FIG. 11 is a flowchart of a method for providing a service for monitoring and evaluating the operational status of a franchise store according to one embodiment.

[0126] Referring to FIG. 11, a method for providing an operation status monitoring and evaluation service for a franchisee according to one embodiment of the present invention can receive first operation information and first consultation information for the first franchisee from a first franchisee terminal (S101).

[0127] In addition, the method for providing a monitoring and evaluation service for the operational status of a franchise store according to one embodiment of the present invention can derive a first franchise evaluation score for the first franchise store based on the first operational information and the first consultation information (S103).

[0128] In addition, the method for providing a monitoring and evaluation service for the operational status of a franchise store according to one embodiment of the present invention can generate operational feedback information for the first franchise store based on the first franchise evaluation score (S105).

[0129] In addition, the method for providing a monitoring and evaluation service of the operational status of a franchise store according to one embodiment of the present invention can transmit the operational feedback information to the first franchise store terminal (S107).

[0130] In addition, the method for providing a monitoring and evaluation service for the operational status of a franchise store according to one embodiment of the present invention may be configured in the same way as the device for providing a monitoring and evaluation service for the operational status of a franchise store disclosed in FIGS. 1 to 10.

[0131] In addition, it may be implemented as a computer program stored on a computer-readable recording medium to execute a method for providing monitoring and evaluation services of the operational status of franchisees in combination with hardware.

[0132] In addition, the method of providing a service for monitoring and evaluating the operational status of a franchisee, combined with hardware, can be implemented using a computer-readable recording medium storing a computer program.

[0133] delete

[0134] FIG. 1 is a block diagram of an electronic device in a network environment according to various embodiments. Referring to FIG. 1, in a network environment, the electronic device may communicate with the electronic device through a first network (e.g., a short-range wireless communication network) or may communicate with at least one of the electronic device or a server through a second network (e.g., a long-range wireless communication network). According to one embodiment, the electronic device may communicate with the electronic device through a server.

[0135] According to one embodiment, the electronic device may include components such as a processor, memory, input module, sound output module, display module, audio module, sensor module, interface, connection terminal, haptic module, camera module, power management module, battery, communication module, and subscriber identification module. In certain examples, at least one of these components may be omitted or other components may be added. Additionally, in some examples, these components may be integrated and used. The electronic device may also be referred to as a client, terminal, or peer.

[0136] A processor can control other components (e.g., hardware or software components) connected to an electronic device and perform various data processing and operations primarily by executing software (e.g., programs). Generally, a processor stores commands or data received from other components (e.g., sensor modules or communication modules) in volatile memory and performs various operations or data processing tasks by processing the stored commands and data. It can also store the data generated as a result of processing in non-volatile memory. By doing so, the processor can control the functions of the electronic device and perform necessary tasks by processing data.

[0137] According to one embodiment, the processor may include a main processor (e.g., a central processing unit or an application processor) or an auxiliary processor capable of operating independently or together therewith (e.g., a graphic processing unit (GPU), a neural processing unit (NPU), an image signal processor, a sensor hub processor, or a communication processor). For example, if an electronic device includes a main processor and an auxiliary processor, the auxiliary processor may be configured to use lower power than the main processor or to be specialized for a specified function. The auxiliary processor may be implemented separately from the main processor or as part thereof.

[0138] A coprocessor is a component that plays a crucial role within an electronic device. It operates either as an auxiliary to the main processor or works in conjunction with it to control functions or states related to other components (e.g., display modules, sensor modules, or communication modules). For instance, the coprocessor can take over the main processor's role when the main processor is in an inactive state (e.g., sleep), and can work alongside the main processor to control various functions and states when the main processor is active (e.g., application execution). By performing these roles, the coprocessor can enhance the performance and increase the efficiency of the electronic device.

[0139] According to some examples, auxiliary processors (e.g., neural network processing units) with hardware structures specialized for processing artificial intelligence models may be included. Artificial intelligence models can be generated through machine learning. This learning may take place on the electronic device itself or through a separate server (e.g., external server, cloud server). Learning algorithms may include various forms such as supervised learning, unsupervised learning, semi-supervised learning, or reinforcement learning.

[0140] An artificial intelligence model may include multiple artificial neural network layers. These artificial neural networks may be a Deep Neural Network (DNN), a Convolutional Neural Network (CNN), a Recurrent Neural Network (RNN), a Restricted Boltzmann Machine (RBM), a Deep Belief Network (DBN), a Bidirectional Recurrent Deep Neural Network (BRDNN), a Deep Q-Network (DQN), or a combination of these methods. However, these examples are not limited.

[0141] Artificial intelligence models may include software structures additionally or as a substitute in addition to hardware structures.

[0142] Memory is an important component used within electronic devices that performs the role of storing various data. This data primarily consists of input or output data for instructions related to software programs. Memory is classified into volatile and non-volatile memory. While stored data in volatile memory is lost when the power is turned off, non-volatile memory can preserve data even when the power is off.

[0143] A program consists of software and can be stored in memory. This program may include components such as an operating system, middleware, and applications. The operating system functions as the core software of a computer system, managing efficient interaction between hardware and software and providing an interface between the user and computer resources. Middleware acts as an intermediate layer of software, facilitating communication between applications and hardware or other software. Applications are software programs designed to perform specific tasks, providing functions tailored to user needs. These components are stored in memory and executed, supporting the operation of the computer system and providing functions to the user.

[0144] An input module can provide the functionality for an electronic device component (e.g., a processor) to receive commands or data transmitted from outside the electronic device (e.g., a user). This module can be composed of various input devices. For example, elements such as microphones, mice, keyboards, and buttons may be included. Additionally, digital pens, such as stylus pens, can also be used as input modules. The input module facilitates smooth interaction between the user and the electronic device and functions to allow the user to transmit commands or input data. Voice commands are transmitted via a microphone, and actions such as clicking, scrolling, and key presses can be performed using a mouse and keyboard. Furthermore, specific functions can be executed by pressing a button, or drawings or handwriting can be input directly into the electronic device using a stylus pen. The input module can transmit user commands and input to the electronic device for processing.

[0145] An audio output module can output audio signals to the outside of an electronic device. This module may include elements such as speakers or receivers. Speakers are primarily used for general purposes, such as multimedia playback or recording playback. Receivers are primarily used to receive incoming calls. Additionally, the audio output module can deliver sound to the user by outputting audio signals generated by the electronic device to the outside. Various multimedia content, such as music, movies, and games, can be played through speakers, while phone calls or notification sounds can be received through receivers. Through this, users can have various auditory experiences, such as listening to sounds or hearing voices.

[0146] Display modules can visually present information to users. For example, displays can be used to show various content such as text, images, and videos. Alternatively, holographic devices can provide a three-dimensional and realistic visual experience. Information can also be projected onto a large screen using a projector. These display modules enable visual interaction between electronic devices and users.

[0147] Audio modules convert sound acquired from external sources into electronic signals, enabling them to be processed by electronic devices. They can capture sound using microphones or other input modules and convert it into electrical signals. Conversely, electrical signals generated by electronic devices can be converted into sound and output through the audio module. These audio modules can process and play various sounds, such as music, voice calls, and multimedia content. Additionally, audio modules can connect to external electronic devices (e.g., speakers or headphones) to output sound generated by the devices. This allows users to listen to music, movies, calls, and more through the audio module. Furthermore, audio modules can be connected to external electronic devices via wireless connections, providing users with more convenient sound output options.

[0148] Sensor modules can perform the role of monitoring the operating status of electronic devices or detecting changes in the external environment. For example, gesture sensors can detect user movements, and gyroscope sensors can detect rotational motion. Barometric pressure sensors can detect changes in atmospheric pressure, and magnetic sensors can detect changes in magnetic fields. Accelerometer sensors detect acceleration, and grip sensors can detect contact between the device and the user. Proximity sensors detect the distance to objects around the device, and color sensors can detect color information. Infrared (IR) sensors detect infrared signals, and biometric sensors can detect the user's vital signs (e.g., heart rate). Temperature sensors detect ambient temperature, humidity sensors detect humidity levels, and light sensors detect ambient light intensity. Sensor modules can generate electrical signals or data values ​​based on the detected state, which can then be utilized by the electronic device. Through this, the electronic device can interact with the surrounding environment and provide users with better functionality and convenience.

[0149] Interfaces enable interaction between electronic devices and allow for the exchange of data or signals. The HDMI interface is used for high-definition multimedia transmission, while the USB interface can be used for connecting with various devices and transmitting data. The SD card interface supports connection with memory cards, and the audio interface can provide functions for transmitting sound signals. Interfaces adhere to specific protocols to ensure compatibility and interoperability between electronic devices. Through this, users can perform tasks such as sharing data with other devices, transferring files, connecting external storage devices, and controlling multimedia devices. Interfaces play a role in enhancing the expandability and versatility of electronic devices by providing various functions.

[0150] Connection terminals are a crucial element for the physical connection of electronic devices with the outside world. HDMI connectors provide an interface for transmitting high-definition audio and video signals, while USB connectors are used for connecting with various devices and transferring data. SD card connectors support physical connections with memory cards, and audio connectors (e.g., headphone connectors) provide connections with audio devices. Furthermore, connection terminals establish physical connections through connectors for data transfer or signal transmission between electronic devices. This enables users to share data with other devices, connect external storage devices, and connect audio devices. Connection terminals ensure the expandability and compatibility of electronic devices and can provide users with various connection options.

[0151] Haptic modules can convert electrical signals generated by electronic devices into mechanical stimuli or convert mechanical stimuli into electrical stimuli to deliver them to the user. They can generate mechanical stimuli, such as vibrations or movements, using motors. Piezoelectric elements are devices that deform in response to electrical signals and can stimulate the user's sense of touch. Additionally, electrical signals can be transmitted to the user's sense of touch through electrical stimulation devices. Furthermore, haptic modules can improve interaction between electronic devices and users and provide users with a more immersive experience. For example, they can be used to convey the intensity of action or changes in the environment via vibration in game controllers, or to provide feedback via vibration on touchscreens. Haptic modules enhance the user interface of electronic devices and can be utilized to improve the user experience across various application fields.

[0152] Camera modules can provide the function of capturing photos or videos. Lenses play the role of collecting and regulating light to form accurate images. Image sensors can generate digital images by converting the light collected from the lens into electrical signals. Image signal processors process digital images and can form the final image by optimizing elements such as resolution, color, and brightness. Flashes can improve the quality of captured images by providing additional lighting in dark environments. Furthermore, camera modules can be utilized for various purposes and can be integrated into a wide range of electronic devices, including digital cameras, smartphones, tablets, and wearable devices. Through camera modules, users can record moments and capture, save, and share photos or videos. As an essential component for digital video recording, camera modules are widely used in modern electronic devices.

[0153] Power management modules can manage power consumption by regulating and optimizing the power supplied to electronic devices. Power management ICs, such as PMICs, provide functions like voltage regulation, current control, and power conversion to coordinate various components within electronic devices so that they receive appropriate power. This enables efficient power management, such as minimizing power consumption and extending battery life. Furthermore, power management modules can include various functions such as charging, battery management, and power-saving modes, thereby improving the performance and energy efficiency of electronic devices. Power management modules can be a critical factor in ensuring the stable operation of electronic devices and long battery life. Through this, users can utilize electronic devices efficiently and enjoy the benefits of long-term power consumption and battery management.

[0154] Batteries serve the role of storing energy in electronic devices and supplying power when needed. Non-rechargeable primary batteries require replacement after a single use, whereas rechargeable secondary batteries can be repeatedly charged and discharged. Fuel cells are a special type of battery that generates electrical energy using external fuel. Batteries are used in a wide variety of electronic devices, such as mobile devices, laptops, electric vehicles, and drones, and can be essential for sustaining the operation of these devices. Batteries offer long-term usability and can serve as a reliable power source for portable and mobile electronic devices. Users of electronic devices can maintain power supply by charging or replacing batteries, thereby ensuring a seamless user experience.

[0155] Communication modules are used to facilitate data exchange between electronic devices and other devices or networks. Wired communication channels transmit data between electronic devices via wires, while wireless communication channels can transmit data using radio waves. Through this, users can perform various communication functions such as data sharing, remote control, internet access, and message transmission. Furthermore, communication modules operate independently, separate from the processor, and include one or more communication processors specialized for communication. These processors can handle the transmission, reception, and processing of data for efficient communication. Communication modules support various protocols and technologies to enable seamless interaction with other devices or networks. Consequently, users can utilize various communication functions through the communication module, such as rapid data exchange, remote control, and information sharing.

[0156] According to an actual implementation example, the communication module may include a wireless communication module (e.g., a cellular communication module, a short-range wireless communication module, a GNSS communication module) or a wired communication module (e.g., a LAN communication module, a power line communication module). The corresponding module among these communication modules may communicate with an external electronic device through a first network (e.g., a short-range communication network such as Bluetooth, WiFi Direct, or IrDA) or a second network (e.g., a legacy cellular network, a 5G network, a next-generation communication network, the Internet, a LAN, or a WAN).

[0157] These various types of communication modules can be integrated into multiple components, such as a single chip or multiple chips, or implemented as separate components. Wireless communication modules can identify or authenticate electronic devices within a communication network, such as a first or second network, by utilizing subscriber information (e.g., International Mobile Subscriber Identifier (IMSI)) stored in a subscriber identification module. This enables users to perform secure and reliable communication through various communication networks.

[0158] The wireless communication module can support 5G networks and next-generation communication technologies following 4G networks. For example, by utilizing NR access technology, it can support various functions such as enhanced MBB (eMultiple Mobile Broadband), massive machine communication (mMTC), and reliable low-latency communication (URLLC). Additionally, the wireless communication module can achieve high data transmission rates by utilizing high-frequency bands (e.g., mmWave bands). To this end, it can support various technologies such as beamforming, massive array multiple input / output (MIMO), full-dimensional multiple input / output (FD-MIMO), array antennas, analog beamforming, and massive antennas. Furthermore, the wireless communication module can meet various requirements demanded by electronic devices, external electronic devices, or network systems (e.g., a secondary network).

[0159] For example, the wireless communication module can support requirements such as a maximum data transfer rate for eMBB (e.g., 20 Gbps or higher), loss coverage for mMTC (e.g., 164 dB or lower), and minimum U-plane delay for URLLC (e.g., downlink (DL) and uplink (UL) each of 0.5 ms or less, or round trip 1 ms or less). This enables the wireless communication module to provide a faster and more stable communication environment and deliver excellent performance in various applications.

[0160] An antenna module can perform the function of transmitting or receiving signals or power to an external source (e.g., an external electronic device). According to one embodiment, the antenna module may include a radiator antenna consisting of a conductor or a conductive pattern formed on a substrate (e.g., a PCB). Additionally, the antenna module may include multiple antennas (e.g., an array antenna). In this case, the communication module may select a suitable one from the plurality of antennas to select at least one antenna suitable for a specific communication method used in a communication network, such as a first network or a second network. Through this selected antenna, signals or power can be transmitted or received between the communication module and the external electronic device. Furthermore, in some embodiments, other components such as an RFIC (Radio Frequency Integrated Circuit) may be added as components of the antenna module in addition to the radiator.

[0161] According to various embodiments, the antenna module may comprise a mmWave antenna module. According to an example, the mmWave antenna module is placed on a printed circuit board, which may be adjacent to or located on a first surface (e.g., bottom surface) to support a high-frequency band (e.g., mmWave band) such as an RFIC. Additionally, a plurality of antennas (e.g., array antennas) capable of transmitting or receiving signals of a specified high-frequency band may be located on a second surface (e.g., top surface or side surface) of the printed circuit board.

[0162] According to one embodiment, commands or data may be transmitted between an electronic device and an external electronic device through a server connected to a second network. The external electronic device may be a device of the same type as or different from the electronic device. For example, all or part of the work to be performed by the electronic device may be executed by one or more external electronic devices. This means that if the electronic device needs to automatically perform a specific function or service, it may request the external electronic device to execute the function or service. Upon receiving such a request, one or more external electronic devices may execute the requested function or service or additional functions and services, and transmit the execution results to the electronic device. The electronic device may use these results as a response to the original request or provide them after further processing.

[0163] To this end, interaction between electronic devices and external electronic devices can be achieved by utilizing technologies such as cloud computing, distributed computing, mobile edge computing (MEC), or client-server computing, for example. Electronic devices can provide ultra-low latency services using methods such as distributed computing or mobile edge computing. As another example, external electronic devices may include IoT devices, and servers may utilize intelligent technologies such as machine learning and neural networks. In some practical applications, external electronic devices or servers may be located on a second network. Based on 5G communication technology and IoT-related technologies, electronic devices can be applied to intelligent services such as smart homes, smart cities, smart cars, and healthcare.

[0164] The server can be connected to an electronic device and provide services to that electronic device. Additionally, it can store and manage information of users who have registered as members by performing a membership registration process, and can provide various functions related to purchasing and payment. Furthermore, the server can share services among users by sharing execution data of service applications running on multiple electronic devices in real time. While this server (108) has a hardware configuration similar to a general web server or WAP server, it may include program modules that perform various functions using languages ​​such as C, C++, Java, Visual Basic, and Visual C in terms of software.

[0165] Furthermore, a server generally refers to a computer system and related computer software (server program) that is connected to an unspecified number of clients or other servers through an open computer network such as the Internet, accepts requests to perform tasks from clients or other servers, and derives and provides results for those tasks. Additionally, a server can be understood as a concept that includes, in addition to the server program, various applications running within the server and various databases (DBs) built internally or externally. Therefore, a server classifies membership registration information and game-related information and data, stores them in a DB, and manages them; such DBs can be implemented either internally or externally to the server.

[0166] Furthermore, the server can be implemented on general server hardware based on various operating systems such as DOS, Windows, Linux, UNIX, and Macintosh, and can utilize server programs tailored to each operating system. Representative examples include websites and IIS (Internet Information Server) used in Windows environments, as well as CERN, NCSA, and Apache used in UNIX environments. Additionally, the server can be integrated with authentication and payment systems related to service user authentication and purchase payments.

[0167] The first network and the second network represent a connection structure capable of exchanging information between each node, such as a terminal and a server, and may also refer to a network connecting a server and an electronic device. Such networks include, but are not limited to, the Internet, LAN, wireless LAN, WAN, PAN, 3G, 4G, LTE, 5G, Wi-Fi, etc.

[0168] The first and second networks may take the form of closed LANs or WANs, but it may be appropriate to utilize the open Internet. The Internet is an open computer network used globally that can provide various services such as TCP / IP protocols and upper-layer protocols like HTTP, Telnet, FTP, DNS, SMTP, SNMP, NFS, and NIS. Through this, the first and second networks operate in an open structure, forming an environment where various computer systems are interconnected based on the Internet.

[0169] A database is a general data structure implemented on a computer system's storage device (hard disk or memory) and can be managed through a database management system (DBMS). Databases can take the form of data storage that allows for the free performance of various operations, such as searching, deleting, editing, and adding data. They can be implemented according to purpose using systems ranging from relational database management systems (RDBMS) like Oracle, Informix, Sybase, and DB2, to object-oriented database management systems (OODBMS) like Gemstone, Orion, and O2, and XML native databases like Excelon, Tamino, and Sekaiju, and can perform their functions by appropriately utilizing fields or elements.

[0170] FIG. 2 is a diagram showing the configuration of a program according to one embodiment.

[0171] FIG. 2 is a block diagram illustrating a program according to various embodiments. According to one embodiment, the program may include an operating system, middleware, or an application executable on said operating system for controlling one or more resources of an electronic device. The operating system may include, for example, Android™, iOS™, Windows™, Symbian™, Tizen™, or Bada™. At least some of the programs may be, for example, preloaded into the electronic device at manufacturing time, or downloaded or updated from an external electronic device (e.g., an electronic device or a server) when used by a user. All or part of the program may include a neural network.

[0172] The operating system can control the management (e.g., allocation or deallocation) of one or more system resources (e.g., processes, memory, or power) of the electronic device. The operating system may additionally or alternatively include one or more driver programs for driving other hardware devices of the electronic device.

[0173] Middleware can provide various functions to applications so that functions or information provided from one or more resources of an electronic device can be used by the application. According to one embodiment, middleware can dynamically delete some existing components or add new components. According to one embodiment, at least a portion of the middleware may be included as part of an operating system or implemented as separate software distinct from the operating system.

[0174] In this specification, neural network, neural network, and network function may be used interchangeably. A neural network may consist of a set of connected computational units, which are generally also referred to as "nodes." Nodes may also be referred to as neurons. A neural network may consist of at least two nodes. These nodes or neurons may be interconnected through one or more "links."

[0175] In a neural network, when two or more nodes are connected by links, they can form a relative relationship between input and output nodes. The concepts of input and output nodes are relative; a node can act as an output node in relation to another node, while simultaneously acting as an input node in relation to another node. The relationship between input and output nodes can be established based on links. One or more output nodes can be connected to an input node via links, and vice versa.

[0176] In a relationship where an input node and an output node are connected through a single link, the output node can determine a value based on the input data. In this case, the nodes interconnecting the input and output nodes may have weights. These weights are variable and can be adjusted by the user or the algorithm to enable the neural network to perform the desired function. For example, if a single output node is connected to multiple input nodes via respective links, the output node can determine the output value by considering the input value and the weights of the links corresponding to those input nodes.

[0177] As mentioned above, a neural network consists of interconnected nodes and links connecting them. Within this network, the characteristics of the neural network can be determined by the number of nodes and links and the weight values ​​assigned to each link. For example, if there are two neural networks with the same number of nodes and links but different weight values ​​between the links, these two neural networks can be recognized as having different characteristics.

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[0179] The embodiments described above may be implemented as hardware components, software components, and / or combinations of hardware and software components. For example, the devices, methods, and components described in the embodiments may be implemented using one or more general-purpose or special-purpose computers, such as, for example, a processor, a controller, an arithmetic logic unit (ALU), a digital signal processor, a microcomputer, a field programmable gate array (FPGA), a programmable logic unit (PLU), a microprocessor, or any other device capable of executing and responding to instructions. The processing unit may execute an operating system (OS) and one or more software applications executed on said operating system. Additionally, the processing unit may access, store, manipulate, process, and generate data in response to the execution of the software. For ease of understanding, the processing unit may be described as being used as a single unit, but those skilled in the art will understand that the processing unit may include multiple processing elements and / or multiple types of processing elements. For example, the processing unit may include multiple processors or one processor and one controller. Additionally, other processing configurations, such as parallel processors, are also possible.

[0180] The method according to the embodiment may be implemented in the form of program instructions that can be executed through various computer means and recorded on a computer-readable medium. The computer-readable medium may include program instructions, data files, data structures, etc., either alone or in combination. The program instructions recorded on the medium may be those specifically designed and configured for the embodiment, or they may be those known and available to those skilled in the art of computer software. Examples of computer-readable recording media include magnetic media such as hard disks, floppy disks, and magnetic tapes; optical recording media such as CD-ROMs and DVDs; magneto-optical media such as floptical disks; and hardware devices specifically configured to store and execute program instructions, such as ROM, RAM, and flash memory. Examples of program instructions include machine code, such as that generated by a compiler, as well as high-level language code that can be executed by a computer using an interpreter, etc. The hardware devices described above may be configured to operate as one or more software modules to perform the operation of the embodiment, and vice versa.

[0181] Software may include computer programs, code, instructions, or a combination of one or more of these, and may configure a processing unit to operate as desired or command the processing unit independently or collectively. Software and / or data may be permanently or temporarily embodied in any type of machine, component, physical device, virtual equipment, computer storage medium or device, or transmitted signal wave so as to be interpreted by the processing unit or to provide instructions or data to the processing unit. Software may be distributed over networked computer systems and may be stored or executed in a distributed manner. Software and data may be stored on one or more computer-readable recording media.

[0182] Although the embodiments have been described above with reference to the limited drawings, those skilled in the art can apply various technical modifications and variations based on the above. For example, suitable results may be achieved even if the described techniques are performed in a different order than described, and / or if the components of the described system, structure, device, circuit, etc. are combined or assembled in a form different from described, or replaced or substituted by other components or equivalents.

[0183] Therefore, other implementations, other embodiments, and equivalents to the claims also fall within the scope of the claims set forth below.

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Claims

Claim 1 In an electronic device, memory; and a processor connected to said memory;The processor includes, wherein the processor receives first operational information and first consultation information regarding the first franchise from the first franchise terminal, derives a first franchise evaluation score regarding the first franchise based on the first operational information and the first consultation information, generates operational feedback information regarding the first franchise based on the first franchise evaluation score, transmits the operational feedback information to the first franchise terminal, wherein the first operational information includes, for the first franchise, first location information, sales information by a preset target period, operating profit information, and franchise product order quantity, and the first consultation information includes, for the first franchise, information regarding consultation history through preset consultation media, and wherein the processor derives a sales score regarding sales performance regarding the first franchise based on the first operational information, derives an operational score regarding the operational status regarding the first franchise based on the first consultation information, and derives the first franchise evaluation score based on the sales score and the operational score. The processor derives, and converts multiple consultation records by consultation medium into text information, tokenizes the text information by each keyword, calculates TF-IDF weights for each tokenized keyword, extracts keywords in order of highest TF-IDF weights up to a preset threshold number as a representative keyword bundle for the corresponding consultation records, derives a positive or negative evaluation for the corresponding consultation records based on the representative keyword bundle through an LLM (Large Language Model) module trained to determine whether the keyword has a positive or negative meaning, and derives the operational score for the first franchise based on the positive or negative evaluation for all consultation records, wherein the processor extracts the region corresponding to the first location information as a target region among regions divided into preset sections based on the first location information, extracts multiple franchises located in the target region as second franchises, and the operational score is derived by the following mathematical formula; OS (Operating Score) refers to the above-mentioned operating score, d_1 refers to the total number of consultation records for the above-mentioned first franchisee, d_2 refers to the number of consultation records corresponding to positive evaluations for the above-mentioned first franchisee, e_1 refers to the average of the total number of consultation records for the above-mentioned second franchisees, e_2 refers to the average of the number of consultation records corresponding to positive evaluations for the above-mentioned second franchisees, and the above-mentioned first franchisee evaluation score is derived by the following mathematical formula, An electronic device characterized in that 1ES (Evaluation Score) refers to the first franchise evaluation score, SS refers to the sales score, and OS refers to the operation score. Claim 2 delete Claim 3 delete Claim 4 delete Claim 5 delete Claim 6 delete Claim 7 delete Claim 8 delete Claim 9 delete Claim 10 delete Claim 11 delete Claim 12 delete Claim 13 delete Claim 14 delete

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