Selling method and selling server

Abstract

To price digital data in consideration of the economic situation in selling the digital data.SOLUTION: A selling server for digital data includes: a training unit 108 which generates a trained model 109 for determining a sale price of digital data, using information on a category of the digital data, information on economy, and reference price of the category, as training data; and a price determination unit which inputs the information on the category of the digital data for sale and the information on economy to the trained model 109 to obtain a sale price of the digital data output from the trained model.SELECTED DRAWING: Figure 3

Description

[Technical field]

[0001] The present invention relates to a sales method and a sales server for selling digital data. [Background technology]

[0002] In recent years, with the evolution of network services, such as the establishment of cloud services and social services, coupled with the widespread use of smartphones, a huge amount of diverse digital data is being generated, distributed, and stored on networks. This digital data is being used to create innovative services and business models, make accurate management decisions, and improve business efficiency, and its importance is increasing day by day.

[0003] A system for selling digital content is disclosed in Patent Document 1. The sales system in Patent Document 1 includes a content server that stores digital content, a price profile database that stores price profile information for determining the price of the digital content, and a billing server that performs billing for purchases of the digital content.

[0004] The price profile information includes parameters (hereinafter referred to as "sales status parameters") indicating the sales status of the digital content, such as the sales volume, profit margin, total profit, and the date and time elapsed since the start of sales, and price information corresponding to the sales status parameters. When an order for the digital content is received, the billing server obtains the sales status of the digital content, and determines the price of the digital content based on the sales status parameters.

[0005] In the sales system described in Patent Document 1, when digital content is sold over a network, the sales price of the digital content is changed based on pre-set sales status parameters, and the sales price at the time an order for the digital content is received is charged to the customer, making it possible to adjust prices according to the sales status of the product. [Prior art documents] [Patent documents]

[0006] [Patent Document 1] JP 2002-304579 A Summary of the Invention [Problem to be solved by the invention]

[0007] In the above patent document, the price of digital content, which is digital data, fluctuates based on a sales status parameter that is set in advance. However, in today's world of vigorous economic activity, the value of digital data fluctuates from moment to moment and is unpredictable, making it difficult to set in advance a sales status parameter that determines the price of the digital data. Therefore, the present invention aims to provide a digital data sales method and sales server that can price digital data taking into account the economic situation.

[0008] In addition, the price of digital data is generally determined by the seller, and it is difficult to judge the appropriateness of the price. Therefore, an object of the present invention is to provide a method and a sales server for selling digital data that can appropriately price the digital data. [Means for solving the problem]

[0009] In order to achieve the above-mentioned object, the present invention is a method for selling digital data, characterized in that it includes a learning step of generating a trained model for determining a buying and selling price of the digital data using information on the category of the digital data, information on the economy, and a reference price for the category as training data, and a price determination step of inputting information on the category of the digital data to be sold and information on the economy into the trained model, and obtaining the buying and selling price of the digital data output from the trained model.

[0010] The method also includes an acquisition step of acquiring information indicating the validity of the buying and selling price from a purchaser or provider of the digital data, and a feedback step of feeding back the information indicating the validity of the buying and selling price to the trained model.

[0011] In addition, in the acquiring step, the purchaser or provider is determined randomly.

[0012] The reference price is determined based on a price received from a purchaser or provider of the digital data.

[0013] The present invention is a digital data sales server comprising: a learning unit that generates a trained model for determining a buying and selling price of the digital data using information on the category of the digital data, information on the economy, and a reference price for the category as training data; and a price determination unit that inputs information on the category of the digital data to be sold and information on the economy into the trained model, and obtains the buying and selling price of the digital data output from the trained model. Effect of the Invention

[0014] According to the present invention, it is possible to price digital data taking into account the economic situation. Also, it is possible to appropriately price digital data. [Brief description of the drawings]

[0015] [Figure 1] 1 is a schematic diagram of a data sales system according to an embodiment of the present invention; [Diagram 2] FIG. 1 shows tables in a database of the data sales system. [Diagram 3] A block diagram showing the functions of a sales server provided in the data sales system. [Figure 4] Main flow diagram of the above sales server [Diagram 5]Price update process flow chart [Figure 6] Correction process flow chart DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0016] DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS A data sales system, a data sales method, and a sales server according to an embodiment of the present invention will be described below with reference to the accompanying drawings.

[0017] <Outline of the data sales system 100> A data sales system 100 according to the present embodiment shown in Fig. 1 (hereinafter referred to as "this system 100") is a system for selling digital data. Here, the digital data is typically data on an individual's daily activities (hereinafter referred to as "individual activity data") and data on a group's activities (hereinafter referred to as "group activity data").

[0018] The individual activity data is classified into a plurality of categories. The representative categories are health care, diet, screen time, learning records, purchase history, and the like. The health care category is related to daily health management, and includes step count data, sleep time data, exercise time data, blood glucose level data, heart rate data, and the like measured daily by a wearable computer worn on the wrist, arm, head, and the like. The diet category is related to daily meals and snacks, and includes meal data in which the contents of meals are recorded, snack data in which the contents of snacks are recorded, and eating out data in which the contents of meals out are recorded, and the like. The screen time category is related to time spent using devices equipped with screens, such as smartphones, personal computers, televisions, and video games, and includes data on the usage time and apps of smartphones and personal computers, data on TV programs and viewing time, and data on video game play time and game software. The learning record category is related to daily learning, and includes data on study time, study subjects, and study amount. The purchase history category relates to daily purchase history (shopping history), and is data on purchased items, amounts, and purchase dates and times.

[0019] The group activity data is also classified into a plurality of categories. The representative categories are research, investigation, development, questionnaires, etc. The research category is a category related to research in companies and universities, and includes data related to various research contents and data related to various experimental results. The investigation category is a category related to investigations conducted in companies, universities, organizations, etc., and includes data related to various investigations. The development category is related to development and know-how in universities and companies, and includes various development data and know-how data. The questionnaire category is related to investigations conducted in companies, universities, organizations, and includes data related to various investigation results.

[0020] The classification of categories is not limited to the above examples, and other categories may be included, or the categories may be further subdivided.

[0021] As shown in FIG. 1, the system 100 is composed of a seller terminal 10 owned by a seller of digital data, a purchaser terminal 30 owned by a purchaser of digital data, and a sales server 50 (hereinafter referred to as "server 50"). The seller terminal 10, the purchaser terminal 30, and the server 50 are capable of communicating with each other via the Internet.

[0022] <Configuration of seller terminal 10> The seller terminal 10 is a smart device such as a smartphone or a tablet terminal, and includes a touch panel display, a communication module, a CPU, and a memory. The touch panel display is a device that functions as a display unit that displays information to the seller and an input reception unit that receives input from the seller. The communication module functions as a communication unit that transmits and receives information to the server 50 via the Internet. The memory functions as a storage unit, and a browser application is pre-stored (installed). The CPU functions as a processing unit that executes the browser application. Such a seller terminal 10 is not limited to a smart device. For example, the seller terminal 10 may be a personal computer having a display that functions as a display unit, a keyboard and a mouse that function as an input reception unit, a memory that functions as a storage unit that stores the browser application, and a CPU that functions as a processing unit that executes the browser application.

[0023] <Configuration of Purchaser Terminal 30> The purchaser terminal 30 is a smart device or a personal computer having the same configuration as the seller terminal 10. Since the purchaser terminal 30 has the same configuration as the seller terminal 10, a description thereof will be omitted here.

[0024] <Server 50 Configuration> The server 50 is a device that sells digital data acquired from a seller to a purchaser. The server 50 is composed of, for example, a web server that communicates with the seller terminal 10 and the purchaser terminal 30, an application server that communicates with the web server and processes the communicated information and data, and a database server that communicates with the application server and updates and searches information in the database 51. Each of these servers includes a communication module that functions as a communication unit that communicates via a network, a memory that functions as a storage unit that stores a program, and a CPU that functions as a processing unit that executes the program.

[0025] <Database 51 Configuration> The server 50 configured as above includes a database 51 that functions as a user information storage unit 101 (FIG. 3) that stores information (hereinafter referred to as "user information") relating to sellers and purchasers (hereinafter referred to as "users"), a digital data storage unit 102 (FIG. 3) that stores digital data, a data information storage unit 103 (FIG. 3) that stores information relating to the digital data (hereinafter referred to as "data information"), and a sales history storage unit 104 (FIG. 3) that stores sales history. Specifically, as shown in FIG. 2, the database 51 is provided with a user master, a digital data table, and a sales history table.

[0026] <User master> The user master is a table that functions as the above-mentioned user information storage unit 101. Here, the user information is typically information regarding the usage authority of the system 100, the user's personal information / group information, and payment information, but may also include other information regarding the user. The information related to the usage authority is a user ID and a password. The user ID is identification information uniquely assigned to each user, and is typically an email address used by the user. The user ID is registered in the user ID field. The password is information for authenticating the usage authority of the system 100, and is registered in the password field. The user's personal information / organization information is the user's name and address. The user's name is registered in the name field, and the address is registered in the address field. The user's personal information / organization information is not limited to the name and address, and may include a phone number, age, sex, and summary information of the organization. The payment information is information used for payment, and includes a user ID for online payment and information about a bank account. A record is added to the user master every time a registration request is received from a user in a user registration process s10 described below, and the user information included in the registration request is registered in the corresponding field.

[0027] <Digital Data Table> The digital data table is a table that functions as the data information storage unit 103. Here, the data information typically includes management information for the digital data, the buying and selling price, and attributes of the digital data, but may also include other information related to the digital data. The management information for digital data includes the data ID, registration date, seller, and storage location of the digital data. The data ID is information for identifying one piece of digital data from other digital data, and is uniquely assigned to that digital data each time it is uploaded. The data ID is registered in the data ID field. The registration date is the date the digital data was uploaded, and is registered in the registration date field. The seller is information for identifying the seller of the digital data, and the user ID of the seller who uploaded the digital data is registered in the seller field. The storage location is the storage address of the uploaded digital data, and is registered in the storage location field. The purchase price is the purchase price of the digital data, and is registered in the purchase price field. In this embodiment, the purchase price of the digital data is determined by a category price determined for each category of the digital data and a data amount price determined according to the amount of data included in the digital data. The attributes of digital data are the title, category, description, and data amount of the digital data. The title of the digital data is registered in the title field. The category of digital data indicates whether the uploaded digital data falls into any of the above-mentioned healthcare data, dietary data, screen time data, learning record data, purchase history data, questionnaire data, research data, survey data, and development know-how. The category is registered in the category field. The description of the digital data is an overview of the uploaded digital data, and is registered in the description field. The data amount is the amount of data contained in the uploaded digital data, and is registered in the data amount field. A record is added to the digital data table every time a digital data registration request is received from a seller in the data registration process s20 described below, and the data information included in the registration request is registered in the corresponding field.

[0028] <Transaction history table> The transaction history table is a table that functions as the sales history storage unit 104. Here, the transaction history is typically a transaction ID, a data ID of the digital data, a purchaser, a transaction price, a transaction date and time, and log data, but may include other information related to the transaction. The transaction ID is information for identifying one transaction from other transactions, and is uniquely assigned each time a transaction occurs. The transaction ID is registered in the transaction ID field. The data ID is a data ID assigned to the digital data that is the subject of the transaction, and is registered in the data ID field. The purchaser is information for identifying the purchaser of the digital data, and the user ID of the purchaser is registered in the purchaser field. The price is the price at the time of the transaction of the digital data that is the subject of the transaction, and is registered in the price field. The transaction date and time is the date and time when the transaction was established, and is registered in the transaction date and time field. The log data is registered with a payment record received from the payment destination. For example, when an online payment system is used, a record of the payment procedure is output from the system. Such a payment record is registered in the log data field. A record is added to the transaction history table when a transaction is concluded in the transaction process s30 described below, and the transaction history of that transaction is registered in the corresponding field.

[0029] <Server 50 main flow> Next, the processing by the server 50 will be described with reference to Figures 4 to 6. As shown in Figure 4, the CPU of the server 50 executes a user registration process s10, a digital data registration process s20 (hereinafter referred to as "data registration process s20"), a transaction process s30, a price update process s40, and a correction process s50.

[0030] <User registration process s10> The user registration process s10 is a process for registering a person who wishes to sell digital data or purchase digital data using the present system 100, i.e., a person who wishes to become a user of the present system 100 (hereinafter also referred to as a "user prospective user"), and is executed when a user registration request is received from the terminal 10, 30 of the user prospective user (s1: yes). (1) Specifically, when the server 50 is accessed by the terminal 10, 30 of a person who wishes to use the service, the server 50 transmits a usage application form to the terminal 10, 30. The usage application form is provided with input boxes for inputting each item of the seller information or the purchaser information (hereinafter referred to as "user information"). (2) The terminal 10, 30 of the person who wishes to use the service displays the received application form on a display. When predetermined information is entered into each of the input boxes, the terminal 10, 30 of the person who wishes to use the service transmits a user registration request including the entered user information to the server 50. (3) When the server 50 receives the user registration request (s1: yes), the server 50 executes a user registration process s10. In the user registration process s10, the server 50 adds a record to the user master and registers the received user information in the added record. In this manner, the server 50 functions as a user information registration unit 105 (FIG. 3) that registers user information.

[0031] <Data registration process s20> The data registration process s20 is a process for registering digital data and data information, and is executed when a request for registering digital data is received from the seller terminal 10 (s2: yes). (1) Specifically, when the server 50 is accessed from the seller terminal 10, the server 50 transmits a digital data registration form to the terminal. The digital data registration form is provided with input boxes for inputting each item of the data information described above, and a selection box for selecting the digital data to be sold. (2) The seller terminal 10 displays the received digital data registration form on the display. When predetermined information is entered into each of the input boxes and the selection box, the seller terminal 10 transmits a digital data registration request including the entered data information and digital data to the server 50. (3) When the server 50 receives the digital data registration request (s2: yes), it executes data registration processing s50. In the data registration processing s50, preprocessing is performed on the received digital data. The preprocessing is a process of converting the digital data into a format suitable for sale, and includes some or all of a security check, a replacement process, a data deletion process, a sorting process, a type conversion process, and an anonymization process. The security check is a process of checking whether a macro incorporated in the received digital data is contaminated with a virus, and if a virus is contaminated, the provider is notified of the fact, and the digital data is returned to the provider or deleted. The replacement process is a process of correcting a garbled character string or converting a null value, etc., to another value or character string. The data deletion process is a process of deleting a value or information when an outlying value, etc., is contaminated in the digital data or when information contrary to public order and morals is contaminated. The anonymization process is a process of deleting personal information or converting it to other information that cannot identify an individual. After the preprocessing, the digital data is stored in a specified storage area. (4) Next, the server 50 adds a record to the digital data table, and registers the received data information in the added record. Note that a method for determining the buying and selling price of the received digital data will be described later. In this manner, the server 50 functions as a data information registration unit 106 (FIG. 3) that registers digital data and data information about the digital data.

[0032] <Transaction processing s30> The transaction process s30 is a process related to a transaction of digital data, and is started when there is an access from the purchaser terminal 30. In the transaction process s30, the server 50 identifies the purchaser terminal 30 that has accessed the server 50 as session information. (1) Specifically, the server 50 transmits a sales page for digital data to the accessing purchaser terminal 30. The sales page typically includes a list of digital data (hereinafter referred to as a "digital data list"). The digital data list is generated by extracting the data ID, purchase price, and attribute information stored in the digital data table. In addition, based on the seller ID stored in the digital data table, seller information may be extracted from the user master, and the seller information may be included in the digital data list as the provider of the digital data. (2) The purchaser terminal 30 displays the received digital data list on the display. (3) When the digital data to be purchased has been decided, the purchaser terminal 30 transmits to the server 50 a purchase request including the data ID of the digital data designated by the purchaser. (4) When the server 50 receives the purchase request, it extracts the purchaser's payment information from the user master and performs payment. In this embodiment, the server 50 transmits a payment request including transaction information to an external online payment system. The transaction information includes the title of the digital data, which is the product name, the purchase price, the purchaser's personal information / organization information, and payment information. When the payment is completed in the online payment system, a payment record is transmitted from the online system. (5) When the server 50 receives the payment record from the online payment system, it adds a record to the sales history table and registers the transaction information and the payment record in that record. In this manner, the server 50 functions as a trading unit 107 (FIG. 3) that trades digital data.

[0033] <Price update process s40> Here, the system 100 is configured so that the buying and selling prices of digital data fluctuate daily depending on the economic situation. Specifically, the server 50 executes a price update process s40 for updating the buying and selling prices. The price update process s40 is executed at a predetermined time when the transaction of digital data is started, and is a process for updating category prices in the buying and selling prices. As shown in Fig. 5, the price update process s40 executes an economic index acquisition process s41, a price determination process s42, and a price registration process s43 in this order.

[0034] The economic index acquisition process s41 is a process for acquiring a numerical value indicating the economic situation (hereinafter referred to as "economic index"). The economic index is price level, the number of companies by industry, and / or the number of bankrupt companies by industry. The economic index acquisition process s41 can acquire the economic index by sending a request through an API published by a provider of the economic index. Alternatively, the server 50 may acquire these economic indices by crawling websites that publish price levels, the number of companies, and / or the number of bankrupt companies, or the economic indices may be acquired by inputting each economic index surveyed by the operating company of the system 100 into the server 50.

[0035] The price determination process s42 is a process for determining the buying and selling price of each piece of digital data managed by the server 50, and includes a category price determination process and an individual calculation process.

[0036] The category price determination process is a process for determining a category price included in the buying and selling price based on the economic index acquired above, and in this embodiment, the category price is determined using machine learning. Specifically, a trained model 109 (FIG. 3) is generated in advance by machine learning, and the economic index acquired in the economic index acquisition process s41 and the category of the digital data are input to the trained model 109, thereby acquiring the category price output from the trained model 109. Here, in generating the trained model 109, machine learning is performed in advance using the economic index acquired by executing the economic index acquisition process s41, the category of digital data sold in the market (hereinafter referred to as "reference digital data"), and the buying and selling price of the reference digital data (hereinafter referred to as "reference buying and selling price") as teacher data to generate the trained model 109. Note that, among the teacher data, the economic index and the category of the reference digital data become input data, and the reference buying and selling price becomes correct answer data. In this way, the server 50 functions as a learning unit 108 (FIG. 3) that performs machine learning. The category price determination process is executed for each type of category managed in the digital data table.

[0037] The individual calculation process is a process for calculating the individual buying and selling prices of digital data managed in server 50, and determines the buying and selling price of each digital data by adding the data volume price to the determined category price. Specifically, the data volume is extracted from one record in the digital data table, and the data volume price is calculated by multiplying the data volume by the fee per data. Then, a category is extracted from the same record, and the data volume price is added to the category price corresponding to the category, thereby calculating the buying and selling price of the digital data managed in that record. The above process is performed for each record in the digital data table, thereby calculating the individual buying and selling prices of the digital data.

[0038] The price registration process is a process for registering the determined buying and selling price in the digital data table.

[0039] In this manner, according to this embodiment, the price update process s40 is executed every day, so that the buying and selling prices of digital data can be updated daily in accordance with the economic situation.

[0040] Furthermore, when new digital data is registered in the above registration process s20, the price of the digital data based on the data volume is added to the category price calculated on the day to calculate the buying and selling price of the digital data. Therefore, according to this embodiment, it is possible to price digital data taking into account the economic situation.

[0041] <Correction process s50> In addition, in the present system 100, the suitability of the buying and selling price is improved by correcting the trained model 109. Specifically, the server 50 executes a correction process s50. The correction process s50 is, for example, a process executed after a transaction is completed, and an evaluation acquisition process s51 and a feedback process s52 are executed in this order as shown in FIG. 6.

[0042] The evaluation acquisition process s51 is a process of acquiring the validity (evaluation) of the buying and selling price of digital data for each category of digital data. For example, the server 50 transmits a questionnaire about the buying and selling price to a plurality of users (sellers and purchasers) selected at random. The questionnaire is a form including the categories of digital data handled in the present system 100 and the category prices. The form also includes a selection box for selecting "high price" or "low price" for each category price of digital data. When the questionnaire is transmitted to the user's terminal 10, 30, the user checks the contents of the questionnaire and selects either "high price" or "low price". When the server 50 receives the input results of the questionnaire from a plurality of users, it tallies the number of "high price" and the number of "low price" for each category. In this way, the server 50 functions as an evaluation acquisition unit 110 (FIG. 3) that acquires evaluations about the buying and selling price for categories of digital data.

[0043] The feedback process s52 is a process of feeding back the evaluation acquired in the evaluation acquisition process s51 to the machine learning. Specifically, the economic index of the day, the category of the digital data, and the category price calculated based on the evaluation result are input to execute the machine learning. A trained model 109 capable of outputting an appropriate category price reflecting the economic situation and actual needs is generated.

[0044] As described above, the data sales system, data sales method, and sales server according to the present embodiment allow for pricing of digital data that takes into account the economic situation. In addition, the digital data can be appropriately priced.

[0045] Although the embodiment of the present invention has been described above, the present invention is not limited to the embodiment, and may be modified as described below.

[0046] <Variation 1> In the above embodiment, the price update process s40 is executed before the start of the digital data transaction, and the correction process s50 is executed after the digital data transaction, but the execution timing of these processes is not particularly limited. Also, the price update process s40 and the correction process s50 may be executed consecutively at the same timing.

[0047] <Variation 2> The economic index, which is information related to the economy, may include a numerical value indicating the economic situation, such as stock prices. The economic information may also include the latest economic news, international issues, and / or information related to the latest trends. This information is quantified by category using, for example, AI based on natural language processing.

[0048] <Variation 3> In addition, the category prices determined by the category price determination process in the above embodiment may be corrected. For example, as described in the above modification 1, the correction may be made by converting the latest economic news, international issues, and the latest trends into numerical values ​​for each category, and multiplying the category prices by the numerical values ​​to correct the category prices.

[0049] <Variation 4> In the above embodiment, a plurality of types of economic indexes are used as input data for machine learning, but the number of economic indexes may be one (for example, only prices).

[0050] <Variation 5> In the above embodiment, an economic index is used as input data for machine learning, but a demand index may be used in addition to or instead of the economic index. The demand index is a numerical value that indicates the need for digital data, and is calculated based on, for example, the sales of each category of digital data or the number of registered digital data products.

[0051] <Variation 6> The input data for the machine learning in the above embodiment may include a description of the digital data and the amount of data.

[0052] <Variation 7> The buying and selling price of digital data may be calculated taking into account the limit high and low prices. For example, if the buying and selling price calculated in the individual calculation process has changed by 1.5 times or more compared to the previous day, it is determined to be the limit high. If it is determined to be the limit high or the limit low in this way, the buying and selling price is set to the buying and selling price calculated by adding / subtracting a predetermined fluctuation value to the selling price of the previous day.

[0053] <Variation 8> The reference buying and selling price may be determined by a survey of users of the system 100. That is, the server 50 may transmit a form including a category of digital data and an input box for inputting a price appropriate for the category to the user's terminal 10, 30, and the price input by the user may be set as the reference buying and selling price.

[0054] <Variation 9> The sales history table may store the evaluation information received from the purchaser terminal 30.

[0055] <Modification 10> The database 51 may include a questionnaire table that functions as a questionnaire result storage unit that stores the questionnaire results acquired from each user. [Explanation of symbols]

[0056] 10. Merchant Terminal 30 Purchaser terminal 50 Servers 51 Database 100 Data provision system

Claims

1. A method for selling digital data, comprising: A learning step of generating a trained model for determining a buying and selling price of the digital data using information on a category of the digital data, information on the economy, and a reference price of the category as training data; A price determination step of inputting information on the category of digital data to be sold and information on the economy into the trained model and obtaining the buying and selling price of the digital data output from the trained model; A method of selling digital data, including:

2. an acquisition step of acquiring information indicating the validity of the purchase price from a purchaser or provider of the digital data; A feedback step of feeding back information indicating the validity of the buying and selling price to the trained model; The method for selling digital data according to claim 1 , comprising:

3. 3. The method for selling digital data according to claim 2, wherein in said acquiring step, said purchaser or provider is determined randomly.

4. The method for selling digital data according to claim 1 , wherein the reference price is determined based on a price received from a purchaser or provider of the digital data.

5. A digital data sales server, A learning unit that generates a trained model for determining a buying and selling price of the digital data using information on a category of the digital data, information on the economy, and a reference price of the category as training data; A price determination unit that inputs information about the category of digital data to be sold and information about the economy into the trained model and obtains the buying and selling price of the digital data output from the trained model; A digital data sales server comprising:

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