Information processing apparatus, information processing method, and information processing program

Abstract

To provide a user with only data having reliability desired by the user.SOLUTION: An information processing server 10 includes: a collection unit 131 which collects data; a determination unit 133 which determines reliability of the data collected by the collection unit 131, by using a determination model; and a transmission control unit 136 which transmits, to a device as an output destination, data which has been determined by the determination unit 133 to have reliability required for each field in the output destination.SELECTED DRAWING: Figure 2

Description

[Technical Field]

[0001] The present invention relates to an information processing device, an information processing method, and an information processing program. [Background technology]

[0002] The network environment has been developed, and users can use circulating data. [Prior art documents] [Non-patent literature]

[0003] [Non-Patent Document 1] Ministry of Internal Affairs and Communications, “Trends Surrounding Fake News,” [Retrieved October 11, 2023], Internet<URL:https: / / www.soumu.go.jp / johotsusintokei / whitepaper / ja / r01 / html / nd114400.html> Summary of the Invention [Problem to be solved by the invention]

[0004] However, due to the huge amount of data being distributed over the network, users often have difficulty distinguishing between correct and unreliable data. For this reason, there has been a demand for only obtaining data that has a desired level of reliability.

[0005] The present invention has been made in consideration of the above, and aims to provide an information processing device, an information processing method, and an information processing program that can provide a user with only data that has the reliability that the user desires. [Means for solving the problem]

[0006] In order to solve the above-mentioned problems and achieve the objectives, the information processing device of the present invention is characterized by having a collection unit that collects data, a judgment unit that uses a judgment model to judge the reliability of the data collected by the collection unit, and a transmission control unit that transmits data that the judgment unit judges to have the desired reliability for each field at the output destination to the output destination device. [Effects of the Invention]

[0007] According to the present invention, it is possible to provide a user with only data that has the reliability desired by the user. [Brief explanation of the drawings]

[0008] [Figure 1] FIG. 1 is a block diagram illustrating an example of a configuration of an information processing system according to an embodiment. [Figure 2] FIG. 2 is a block diagram illustrating an example of the configuration of the information processing server illustrated in FIG. [Figure 3] FIG. 3 is a diagram illustrating an example of the data configuration of the destination data illustrated in FIG. [Figure 4] FIG. 4 is a diagram illustrating the learning of the determination model shown in FIG. [Figure 5] FIG. 5 is a sequence diagram showing a processing procedure of the information processing method according to the embodiment. [Figure 6] FIG. 6 is a diagram illustrating an example of a computer that implements an information processing server by executing a program. DETAILED DESCRIPTION OF THE INVENTION

[0009] Hereinafter, an embodiment of the present invention will be described in detail with reference to the drawings. Note that the present invention is not limited to this embodiment. In addition, in the description of the drawings, the same parts are designated by the same reference numerals.

[0010] [Embodiment Mode] In the embodiment, a determination model is used to determine the reliability of various collected data, and only data having the reliability desired by the user is provided to the user.

[0011] [Information Processing Systems] FIG. 1 is a block diagram illustrating an example of a configuration of an information processing system according to an embodiment.

[0012] 1, an information processing system 100 according to an embodiment includes an information processing server 10 and servers 20A and 20B to which data is output. The server 20A is provided, for example, in an administrative agency A. The server 20B is provided, for example, in a business operator B.

[0013] The information processing server 10 communicates with external servers 30-1 and 30-2 via a network 40. When the external servers are collectively referred to, they will be referred to as external servers 30.

[0014] The information processing server 10 collects data from the external server 30 and evaluates the reliability of the collected data. The information processing server 10 transmits only data that is determined to have the reliability desired by the output destination (the servers 20A and 20B in the example of FIG. 1) to the servers 20A and 20B.

[0015] The information processing server 10 classifies the collected data into categories and determines the reliability of the data for each category. The information processing server 10 transmits only data determined to have the desired reliability for each category at the output destination to the servers 20A and 20B. The categories include, for example, medicine, law, finance, smart cities, factory management, agriculture, and chemistry.

[0016] Administrative agency A desires to transmit data with the highest reliability in the medical field. Information processing server 10 transmits only data in the medical field that it has determined to be the most reliable to server 20A. Entity B also desires to transmit data with standard or higher reliability in the medical and legal fields. Information processing server 10 transmits data in the medical and legal fields that it has determined to be standard or higher reliability to server 20B.

[0017] This allows the output destination to receive data with a desired reliability for each field.

[0018] [Information processing server] Next, a description will be given of the information processing server 10 shown in Fig. 2. Fig. 2 is a block diagram showing an example of the configuration of the information processing server 10 shown in Fig. 1.

[0019] 2, the information processing server 10 includes, for example, a communication unit 11, a storage unit 12, and a control unit 13. Note that the information processing server 10 may be connected to input devices such as a mouse and a keyboard, and output devices such as a display and a speaker.

[0020] The communication unit 11 controls communications related to various types of information. For example, the communication unit 11 controls communications with the external server 30 and communications with the servers 20A and 20B. The communication unit 11 receives various types of information from the external server 30 and outputs the information to the control unit 13. The communication unit 11 communicates with the servers 20A and 20B, and transmits reliability data desired for each field at the output destination to the servers 20A and 20B.

[0021] The storage unit 12 stores data and programs necessary for various processes by the control unit 13. For example, the storage unit 12 may be a semiconductor memory element such as a random access memory (RAM) or a flash memory, or a storage device such as a hard disk or an optical disk. For example, the storage unit 12 has destination data 121, collected data 122, category-classified data 123, and reliability-determined data 124.

[0022] The destination data 121 is information indicating the reliability of data desired by the servers 20A and 20B that provide the data. Fig. 3 is a diagram showing an example of the data configuration of the destination data 121 shown in Fig. 2.

[0023] 3, the destination data 121 includes, for example, items such as server identification information, identification information for each field, and the reliability of the desired data in that field. Information on these items is registered, for example, during communication with the servers 20A and 20B that provide the data.

[0024] For example, the server of administrative agency A is registered as wanting the most reliable data in the medical field and the most reliable data in the legal field, while the server of business operator B is registered as wanting data with above-standard reliability in the legal field and data with above-standard reliability in the medical field.

[0025] The collected data 122 is various data collected by the information processing server 10 from the external server 30.

[0026] The field-classified data 123 is data collected by the information processing server 10, and is data associated with information indicating the field classified by a field classification unit 132 (described later).

[0027] The reliability-determined data 124 is data in which the field has been classified by the field-classified data 123 and to which a reliability determined by a determination unit 133 (described later) has been assigned.

[0028] The control unit 13 has an internal memory for storing programs that define various processing procedures and necessary data, and executes various processes using these. Here, the control unit 13 may be, for example, an electronic circuit such as a CPU (Central Processing Unit) or an MPU (Micro Processing Unit), or an integrated circuit such as an ASIC (Application Specific Integrated Circuit) or an FPGA (Field Programmable Gate Array).

[0029] The control unit 13 includes a collection unit 131 , a category classification unit 132 , a determination unit 133 , and a transmission control unit 136 .

[0030] The collection unit 131 collects various data from the external server 30 via the communication unit 11. The collection unit 131 collects information published on the network. The data collected by the collection unit 131 is stored in the storage unit 12 as collected data 122.

[0031] The field classification unit 132 is provided before the determination unit 133. The field classification unit 132 classifies the field of the data collected by the collection unit 131. The field classification unit 132 assigns information indicating the field to the data collected by the collection unit 131, and stores the data in the memory unit 12 as field-classified data 123. The field classification unit 132 classifies the field to which the data belongs based on the title, frequently used terms, drawings, the industry of the publisher, etc. The field classification unit 132 may classify the data using a trained classifier. The field classification unit 132 classifies whether the data belongs to a field of medicine, law, finance, smart city, factory management, agriculture, or chemistry.

[0032] The determination unit 133 determines the reliability of each data item using a determination model provided for each field, such as medicine, law, finance, smart cities, factory management, agriculture, or chemistry. The determination unit 133 includes a sorting unit 134, a first determination model 135-1, a second determination model 135-2, and a third determination model 135-3. The first determination model 135-1 corresponds to the "medical" field, the second determination model 135-2 corresponds to the "law" field, and the third determination model 135-3 corresponds to the "smart city" field. The determination unit 133 further includes determination models (not shown) specialized for the fields of finance, factory management, agriculture, or chemistry.

[0033] Here, the determination unit 133 may provide a preprocessing summary model before each determination model or before the allocation unit 134. For example, the summary model is a natural language processing model (e.g., a large-scale language model (LLM)) trained using a large amount of text data so as to output a summary of an input sentence. The determination unit 133 may generate a summary of each piece of data collected by the collection unit 131 using the summary model, and input the summary generated by the summary model to the first determination model 135-1, the second determination model 135-2, and the third determination model 135-3.

[0034] The allocation unit 134 allocates the data collected by the collection unit 131 to each judgment model (e.g., first judgment model 135-1, second judgment model 135-2, third judgment model 135-3) according to the field classified by the field classification unit 132.

[0035] The allocating unit 134 inputs only data classified into the medical field by the field classification unit 132 into a first determination model 135-1 corresponding to the medical field. The allocating unit 134 inputs only data classified into the legal field by the field classification unit 132 into a second determination model 135-2 corresponding to the legal field. The allocating unit 134 inputs only data classified into the smart city field by the field classification unit 132 into a third determination model 135-3 corresponding to the smart city field.

[0036] The first judgment model 135-1, the second judgment model 135-2, and the third judgment model 135-3 are machine learning models that, when data is input, output the reliability of the input data. In this case, a prompt is set in the first judgment model 135-1, the second judgment model 135-2, and the third judgment model 135-3 to instruct the model to determine whether the reliability of the input data is highest, high, standard, or low, and output the result in a predetermined format.

[0037] The first judgment model 135-1, the second judgment model 135-2, and the third judgment model 135-3 are models obtained by fine-tuning a natural language processing model (for example, LLM) trained using a large amount of text data, using the training data described below. The first judgment model 135-1, the second judgment model 135-2, and the third judgment model 135-3 are machine learning models obtained by performing machine learning using peer-reviewed papers in a predetermined field, academic books in a predetermined field, the contents of national examinations in a predetermined field, and publications from administrative agencies that have jurisdiction over a predetermined field.

[0038] Fig. 4 is a diagram illustrating the learning of the first determination model 135-1 shown in Fig. 2. When the field to which the first determination model 135-1 corresponds is medicine, as shown in Fig. 4, machine learning is performed on the first determination model 135-1 using peer-reviewed papers T11 in the medical field, academic books T12 in the medical field, publications T13 from administrative agencies that have jurisdiction over the medical field, and the contents of national medical examinations as training data T1.

[0039] When a peer-reviewed paper T11 in the medical field, an academic book T12 in the medical field, a publication T13 from an administrative agency having jurisdiction over the medical field, or the contents of a national medical examination are input into the first judgment model 135-1, the parameter update unit 50 updates the parameters of the first judgment model 135-1 so as to output the highest reliability.

[0040] The first judgment model 135-1 compares the words and contexts contained in, for example, peer-reviewed medical papers T11, academic books T12, publications T13 from administrative agencies with jurisdiction over the medical field, and the contents of national medical examinations with the words and contexts contained in the input data, thereby determining the reliability of the input data as, for example, highest, high, standard, or low. Specifically, the first judgment model 135-1 calculates the similarity between the words and contexts contained in the training data T1 and the words and contexts contained in the input data based on the feature vectors of the training data T1 and the feature vectors of the input data, and determines the reliability of the input data based on the calculated similarity. For example, a range of similarity is set corresponding to four levels of data reliability, for example, highest, high, standard, or low.

[0041] The parameter update unit 50 may be provided in the information processing server 10, or may be provided in a device different from the information processing server 10. The first determination model 135-1, whose parameters have been optimized by the parameter update unit 50, is applied to the determination unit 133 of the information processing server 10.

[0042] Similarly, second determination model 135-2 corresponds to, for example, the legal field, and machine learning is performed using peer-reviewed papers in the legal field, academic books in the legal field, publications from administrative agencies with jurisdiction over the legal field, and the contents of legal national examinations as training data. When peer-reviewed papers in the legal field, academic books in the legal field, publications from administrative agencies with jurisdiction over the legal field, and the contents of legal national examinations are input to second determination model 135-2, parameters of second determination model 135-2 are updated so as to output the highest reliability.

[0043] The third determination model 135-3 corresponds to, for example, the smart city field, and machine learning is performed using peer-reviewed papers in the smart city field, academic books in the smart city field, publications from administrative agencies with jurisdiction over the smart city field, and the contents of qualification exams required for engineers building smart cities as training data. When peer-reviewed papers in the smart city field, academic books in the smart city field, publications from administrative agencies with jurisdiction over the smart city field, and qualification exams required for engineers building smart cities are input to the second determination model 135-3, the parameters of the third determination model 135-3 are updated so as to output the highest reliability.

[0044] The determination unit 133 assigns information indicating the field into which the data has been classified by the field-classified data 123 and the determined reliability to the data whose reliability has been determined, and stores the data in the memory unit 12 as reliability-determined data 124.

[0045] The transmission control unit 135 transmits the data that has been determined by the determination unit 133 to have the reliability desired for each field at the output destination to the output destination device (servers 20A, 20B).

[0046] For example, when server 20A requests transmission of data in the medical field, transmission control unit 135 transmits to server 20A only the medical field data requested for transmission that has the highest reliability among reliability-determined data 124. When server 20B requests transmission of data in the legal field, transmission control unit 135 transmits to server 20B only the legal field data requested for transmission that has a reliability of standard or higher among reliability-determined data 124.

[0047] [Processing Overview] Fig. 5 is a sequence diagram showing the processing procedure of the information processing method according to the embodiment. In the example of Fig. 5, a case where a transmission request is made from servers 20A and 20B will be described.

[0048] The information processing server 10 communicates with the external server 30 and collects data (step S1). In the information processing server 10, the field classification unit 132 classifies the fields of the collected data (step S2). In the information processing server 210, the allocation unit 134 allocates the collected data to each determination model according to the fields classified by the field classification unit 132 (step S3).

[0049] The information processing server 10 determines the reliability of the assigned data using each determination model (step S4).

[0050] Based on the reliability determined by the determination unit 133, the transmission control unit 136 transmits data (reliability-determined data) having the desired reliability for each field to each of the transmission source servers 20A and 20B (steps S5 and S6).

[0051] [Effects of the embodiment] In this way, the information processing server 10 according to the embodiment uses a judgment model (e.g., the first judgment model 135-1, the second judgment model 135-2, the third judgment model 135-3) to judge the reliability of the collected data, and based on the judgment result, transmits data having the desired reliability for each field at the output destination to the output destination device (e.g., servers 20A, 20B).

[0052] Therefore, the information processing server 10 provides the user with only data that has the reliability that the user desires. In other words, the user can appropriately obtain data that has the reliability that the user desires without having to sort through a huge amount of data by himself / herself.

[0053] Furthermore, the judgment models (for example, the first judgment model 135-1, the second judgment model 135-2, and the third judgment model 135-3) are machine learning models that are obtained by performing machine learning for each of the predetermined fields using peer-reviewed papers in the predetermined field, academic books in the predetermined field, the contents of national examinations in the predetermined field, and publications from administrative agencies that have jurisdiction over the predetermined field. By using these judgment models, the information processing server 10 can appropriately evaluate the reliability of data.

[0054] In addition, the information processing server 10 further provides a field classification unit 132 in front of the judgment unit 133 that classifies the fields of the collected data so that data in a specified field can be output to the judgment unit 133, thereby improving the accuracy of the reliability evaluation by the judgment unit 133.

[0055] The information processing server 10 then classifies the data into categories and uses each judgment model to determine the reliability for each category, thereby transmitting the reliability data desired by each server 20A, 20B for each category to the servers 20A, 20B.

[0056] The determination unit 133 may be configured to have only one determination model. In this case, the category classification unit 132 classifies the categories of the data collected by the collection unit 131, and outputs only the data in the category set in this determination model to the determination unit 133. In this case, the determination unit 133 can omit the sorting unit 134.

[0057] [System configuration of the embodiment] The information processing server 10 is a functional concept and does not necessarily have to be physically configured as shown in the figure. In other words, the specific form of distribution and integration of the functions of the information processing server 10 is not limited to that shown in the figure, and all or part of it can be functionally or physically distributed or integrated in any unit depending on various loads, usage conditions, etc.

[0058] Furthermore, all or any part of the processes performed in the information processing server 10 may be realized by a CPU, a GPU (Graphics Processing Unit), and a program analyzed and executed by the CPU and the GPU. Furthermore, each process performed in the information processing server 10 may be realized as hardware using wired logic.

[0059] Furthermore, among the processes described in the embodiments, all or part of the processes described as being performed automatically can be performed manually. Alternatively, all or part of the processes described as being performed manually can be performed automatically using a known method. In addition, the processing procedures, control procedures, specific names, and information including various data and parameters described above and illustrated can be changed as appropriate unless otherwise specified.

[0060] [program] 6 is a diagram showing an example of a computer in which the information processing server 10 is realized by executing a program. The computer 1000 has, for example, a memory 1010 and a CPU 1020. The computer 1000 also has a hard disk drive interface 1030, a disk drive interface 1040, a serial port interface 1050, a video adapter 1060, and a network interface 1070. These components are connected by a bus 1080.

[0061] The memory 1010 includes a ROM 1011 and a RAM 1012. The ROM 1011 stores a boot program such as a BIOS (Basic Input Output System). The hard disk drive interface 1030 is connected to a hard disk drive 1090. The disk drive interface 1040 is connected to a disk drive 1100. A removable storage medium such as a magnetic disk or optical disk is inserted into the disk drive 1100. The serial port interface 1050 is connected to a mouse 1110 and a keyboard 1120, for example. The video adapter 1060 is connected to a display 1130, for example.

[0062] The hard disk drive 1090 stores, for example, an OS (Operating System) 1091, an application program 1092, a program module 1093, and program data 1094. That is, a program that defines each process of the information processing server 10 is implemented as a program module 1093 in which code executable by the computer 1000 is written. The program module 1093 is stored, for example, in the hard disk drive 1090. For example, a program module 1093 for executing the same process as the functional configuration of the information processing server 10 is stored in the hard disk drive 1090. Note that the hard disk drive 1090 may be replaced with an SSD (Solid State Drive).

[0063] Furthermore, setting data used in the processing of the above-described embodiment is stored as program data 1094, for example, in memory 1010 or hard disk drive 1090. Then, CPU 1020 reads program module 1093 and program data 1094 stored in memory 1010 or hard disk drive 1090 into RAM 1012 as necessary and executes them.

[0064] The program module 1093 and program data 1094 are not limited to being stored in the hard disk drive 1090, but may also be stored in, for example, a removable storage medium and read by the CPU 1020 via the disk drive 1100 or the like. Alternatively, the program module 1093 and program data 1094 may be stored in another computer connected via a network (such as a local area network (LAN) or a wide area network (WAN)). The program module 1093 and program data 1094 may then be read by the CPU 1020 from the other computer via the network interface 1070.

[0065] Although the present invention has been described above as an embodiment, the present invention is not limited to the descriptions and drawings that form part of the disclosure of the present invention. In other words, other embodiments, examples, and operational techniques that can be made by those skilled in the art based on the present invention are all included in the scope of the present invention. [Explanation of symbols]

[0066] 10 Information Processing Server 11 Communications Department 12 Storage section 13 Control Unit 20A, 20B Server 30, 30-1, 30-2 External Server 100 Information Processing Systems 121 Destination Data 122 Collected Data 123 Category-Classified Data 124 Reliability-judged data 131 Collection Department 132 Field Classification Department 133 Judgment section 134 Distribution Department 135-1 First judgment model 135-2 Second Judgment Model 135-3 Third Judgment Model 136 Transmission control section

Claims

1. a collection unit that collects data; a determination unit that determines the reliability of the data collected by the collection unit using a determination model; a transmission control unit that transmits the data that has been determined by the determination unit to have a desired reliability for each field at the output destination to the device at the output destination; An information processing device comprising:

2. The information processing device according to claim 1, characterized in that the judgment model is a machine learning model that, when data is input, outputs the reliability of the input data, and is a machine learning model in which machine learning is performed using peer-reviewed papers in a specified field, academic books in the specified field, the contents of national examinations in the specified field, and publications of administrative agencies that have jurisdiction over the specified field.

3. The information processing device according to claim 1 , wherein the field is medicine, law, finance, smart cities, factory management, agriculture, or chemistry.

4. The information processing device according to claim 1, further comprising a classification unit in front of the judgment unit, which classifies the fields of the data collected by the collection unit and outputs only data in the fields set in the judgment model to the judgment unit.

5. The judgment models are provided according to the fields of medicine, law, finance, smart cities, factory management, agriculture, or chemistry, a classification unit disposed before the determination unit, which classifies the category of the data collected by the collection unit; 2. The information processing apparatus according to claim 1, wherein the determining unit includes a distributing unit that distributes the data collected by the collecting unit to each determination model according to the field classified by the classifying unit.

6. An information processing method executed by an information processing device, collecting data; determining the reliability of the data collected in the collecting step using a decision model; a step of transmitting the data determined in the determining step to have a desired reliability for each field at the output destination to the device at the output destination; An information processing method comprising:

7. collecting data; determining the reliability of the data collected in the collecting step using a decision model; a step of transmitting the data determined in the determining step to have a desired reliability for each field at the output destination to the device at the output destination; An information processing program that causes a computer to execute the above.

Images