Information processing device, information processing method, and information processing program

Abstract

To provide an information processing device, an information processing method, and an information processing program that allow efficient acquisition of useful information.SOLUTION: An information processing device includes output information generation means and output means. The output information generation means generates output information by using a learning model, an object data analysis result, and both output information and external information which are related to object data. The learning model has learned by machine learning a relationship between both an object data analysis result and relevant information and output information including knowledge obtained based on object data. The output means outputs the output information generated by the output information generation means.SELECTED DRAWING: Figure 5

Description

[Technical Field]

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

[0002] There are technologies that utilize the acquired data. For example, Patent Document 1 describes a technology that acquires operational data from a system to be analyzed and automatically creates a report that includes information indicating an abnormality that has occurred in the operational data and information indicating the cause of the abnormality. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Japanese Patent Publication No. 2023-170715 Summary of the Invention [Problem to be solved by the invention]

[0004] However, the technique described in Patent Document 1 may not be able to efficiently acquire useful information.

[0005] An object of the present disclosure is to provide an information processing device, an information processing method, and an information processing program that can efficiently acquire useful information. [Means for solving the problem]

[0006] The information processing device according to the present disclosure includes a learning model that learns through machine learning the relationship between the analysis results of the target data and related information and output information including knowledge obtained based on the target data, an output information generation means that generates output information using the analysis results of the target data and the output information and external information related to the target data, and an output means that outputs the output information generated by the output information generation means.

[0007] In the information processing method disclosed herein, a computer generates output information using a learning model that has been trained through machine learning to determine the relationship between the analysis results of the target data, related information, and output information including knowledge obtained based on the target data, as well as the analysis results of the target data, output information related to the target data, and external information, and outputs the generated output information.

[0008] The information processing program according to the present disclosure causes a computer to execute an output information generation process that generates output information using a learning model that has been learned through machine learning to determine the relationship between the analysis results of the target data, related information, and output information including knowledge obtained based on the target data, the analysis results of the target data, and output information and external information related to the target data, and an output process that outputs the generated output information. [Effects of the Invention]

[0009] According to the present disclosure, useful information can be obtained efficiently. [Brief explanation of the drawings]

[0010] [Figure 1] FIG. 2 is a block diagram illustrating a functional configuration of an information processing device. [Figure 2] 10 is a flowchart illustrating an operation of the information processing device. [Figure 3] FIG. 1 is an explanatory diagram illustrating an example of an outline of an operation of an information processing device. [Figure 4] FIG. 1 is a block diagram illustrating a configuration of a computer. [Figure 5] FIG. 1 is a block diagram illustrating a main part of an information processing device. DETAILED DESCRIPTION OF THE INVENTION

[0011] In recent years, data collection capabilities have improved due to improvements in the performance of cameras and other sensors and communication devices, as well as the rise of the Internet of Things (IoT) and the increasing number of drones and satellites. As a result, the types, amounts, and frequency of usable data are increasing. Some users analyze this data for purposes such as understanding the situation during disasters and inspecting factory malfunctions. To perform their analytical tasks, users must fully utilize the vast amounts of data they have collected. However, there are a wide variety of data utilization and analysis methods. Furthermore, depending on the application, analysis may require not only the collected data but also highly related information from other domains (e.g., information from different sources and acquisition routes, such as public information from public institutions, news reports from media outlets, and posts on World Wide Web sites such as social networking services (SNS) and Wikipedia®).

[0012] However, with a wide variety of information sources and analytical methods, it is not realistic to manually check all data and translate it into final analysis results. Therefore, even if a huge amount of data is collected, it may only be partially utilized. If only a portion of the data is utilized, there is a risk that the information users truly need will not be extracted. Therefore, it is necessary to effectively utilize massive amounts of data and efficiently obtain the useful information users need.

[0013] Hereinafter, embodiments of the present disclosure will be described with reference to the drawings. In each drawing, the same or corresponding elements are designated by the same reference numerals, and duplicate explanations will be omitted as necessary for clarity. Unless otherwise specified, predetermined values ​​such as predetermined values ​​and threshold values ​​are stored in advance in a storage device accessible from a device that uses the values. Furthermore, unless otherwise specified, the storage unit is composed of one or any number of storage devices.

[0014] 1 is a block diagram illustrating an example of the functional configuration of an information processing device according to the present disclosure. The information processing device 100 of this embodiment includes a data analysis unit 101, a related information acquisition unit 102, an output information generation unit 103, an output unit 104, a learning unit 105, an output information storage unit 106, an external information storage unit 107, and a model storage unit 108.

[0015] The data analysis unit 101 executes a data analysis process to analyze input data to be analyzed (hereinafter also referred to as target data). The data analysis unit 101 can execute the data analysis process on various types of target data. The target data includes, for example, still image data, moving image data, audio data, and system logs.

[0016] The data analysis unit 101 can execute different analysis processes depending on, for example, the type of target data and the type of output information generated by the output information generation unit 103. The information processing device 100 may be configured so that the data analysis unit 101 automatically identifies the type of target data, or may be configured so that the type of target data is identified based on a user's input operation. Furthermore, the information processing device 100 may be configured so that the type of output information is identified based on the identified type of target data, or may be configured so that the type of output information is identified based on a user's input operation.

[0017] It should be noted that the "user input operation" specifically refers to an operation in which a user uses an input device (not shown) such as a keyboard, mouse, or touch panel to input commands or information to the information processing device 100. Executing a process in accordance with commands or information input by such an input operation is referred to as executing a process based on a user input operation.

[0018] In the data analysis process of the target data, the data analysis unit 101 may use previously generated output information stored in the output information storage unit 106 and external information stored in the external information storage unit 107.

[0019] The related information acquisition unit 102 acquires information related to the target data (hereinafter also referred to as related information) based on the analysis result of the target data by the data analysis unit 101. The related information acquisition unit 102 may be configured to automatically acquire the related information based on the analysis result of the target data by the data analysis unit 101, or may be configured to acquire the related information based on a user's input operation. Furthermore, the related information acquisition unit 102 may acquire the related information based on the target data, or may acquire the related information based on the target data and the analysis result of the target data.

[0020] The related information acquisition unit 102 acquires related output information as related information from the output information storage unit 106 .

[0021] In this embodiment, the "related output information" is, for example, output information generated based on the analysis results of data related to the target data. Specifically, if image data of a specific region captured at imaging time T is the target data, image data of the same region captured before imaging time T is included in the data related to the target data. Therefore, output information previously generated based on the analysis results of image data of the same region captured before imaging time T becomes the related output information. In this case, the related output information is not limited to output information generated based on the analysis results of image data of the specific region, but past output information related to the specific region may also be included. For example, the related information acquisition unit 102 acquires past output information related to the specific region as related output information from the output information storage unit 106 based on location information identified by the analysis results of the image data.

[0022] The output information storage unit 106 stores output information previously generated by the information processing device 100 or another information processing device to which the technology of the present disclosure is applied. The output information storage unit 106 may store information generated based on the results of data analysis without applying the technology of the present disclosure. Furthermore, the output information storage unit 106 may be configured in an external device different from the information processing device 100.

[0023] The related information acquisition unit 102 acquires related external information from the external information storage unit 107 as related information.

[0024] In this embodiment, "related external information" is, for example, information acquired from another domain (in other words, information from a different information source or acquisition route). Specifically, if the target data is image data captured of a specific area at an image capture time T, the related external information includes public information about the area provided by public institutions, news reported by news organizations, and posts on websites such as SNS and Wikipedia (registered trademark). The related external information may be publicly available information or information whose disclosure is restricted.

[0025] The external information storage unit 107 stores, for example, public information from public institutions, news reported by news organizations, posts on websites such as social networking sites, etc. The external information storage unit 107 stores in advance data collected from various websites using, for example, web crawling or other techniques.

[0026] In this embodiment, the external information storage unit 107 is included in the information processing device 100. However, the external information storage unit 107 may be configured in an external device different from the information processing device 100. Furthermore, the external information storage unit 107 may be configured by a plurality of storage devices each storing different pieces of external information. For example, the related information acquisition unit 102 may acquire data from a plurality of websites each providing different data and use the data as external information.

[0027] The output information generation unit 103 generates output information using a learning model, the analysis results of the target data, and output information and external information related to the target data. The learning model used by the output information generation unit 103 is a model that has been learned by machine learning to describe the relationship between the analysis results of the target data, related information, and output information including knowledge obtained based on the target data. The output information generation unit 103 uses output information generated based on the analysis results of data related to the target data as output information related to the target data. Furthermore, the output information generation unit 103 uses information from a source different from that of the target data as external information related to the target data.

[0028] For example, the output information generation unit 103 inputs the analysis results of the target data, and the output information and external information related to the target data into a trained learning model. As a result, the output information generation unit 103 obtains the output information output from the learning model. Through this process, the output information generation unit 103 generates the output information.

[0029] In this embodiment, the "output information" generated and output by the information processing device 100 is information (hereinafter also referred to as intelligence) that indicates findings obtained from the analysis results of the target data and related information. Intelligence is, for example, information that a user can use for decision-making in business, projects, etc.

[0030] The output information generation unit 103 can generate output information in various formats. For example, the output information generation unit 103 can generate output information in a text format, a format including charts, such as Word (registered trademark) or PowerPoint (registered trademark), or a Markdown format.

[0031] For example, the output information generating unit 103 can generate, as output information, report data including knowledge obtained based on the target data. The output information generating unit 103 can generate the source of the deliverable in a natural language that is easy for the user to understand, based on the analysis result of the target data and related information related to the target data (information that the user generally refers to in order to create a deliverable such as a report).

[0032] Furthermore, for example, the output information generating unit 103 can generate output information including a command (for example, a character string that instructs a computer to perform a specific process) that reflects knowledge obtained based on the target data.

[0033] The output unit 104 outputs output information. For example, the output unit 104 outputs the output information to a display unit (not shown) such as a display device for display. Also, for example, the output unit 104 outputs the output information to the output information storage unit 106 for storage.

[0034] In this embodiment, the output information generation unit 103 can perform correction processing or determination processing on the generated output information based on an input operation by the user. For example, the output unit 104 outputs and displays the output information generated by the output information generation unit 103 on a display unit (not shown) such as a display device so that the user can check it. When the user performs a correction operation using the input device, the output information generation unit 103 corrects the generated output information based on the user's correction operation. Furthermore, when the user performs a confirmation operation using the input device, the output information generation unit 103 confirms the generated (or corrected) output information based on the user's confirmation operation. Then, the output unit 104 outputs the confirmed output information to the output information storage unit 106 to store it.

[0035] Regarding the output information generated (or corrected) by the output information generating unit 103, when determining whether the output information has been finalized or not, the former is referred to as output information (finalized) and the latter as output information (draft). The output unit 104 can output and display not only the output information (draft) but also the output information (finalized) on a display unit (not shown) such as a display device. The output unit 104 can output and store not only the output information (finalized) but also the output information (draft) in a storage unit (not shown) of the information processing device 100 or an external device.

[0036] The learning unit 105 learns the learning model using the analysis results of the target data, related information (output information and external information) of the target data, and output information (confirmed) as correct answer data. For example, the learning unit 105 learns the learning model using output information (confirmed) generated in the past before the information processing device 100 starts operating (and in the initial operation stage). Also, for example, the learning unit 105 re-learns the learning model using the generated output information (confirmed) after the information processing device 100 starts operating.

[0037] Next, a description will be given of the operation of the information processing device 100. Fig. 2 is a flowchart illustrating an example of the operation of the information processing device according to the present disclosure regarding generation of output information.

[0038] The data analysis unit 101 receives target data to be analyzed and performs data analysis processing on the target data (step S1).

[0039] Next, the related information acquisition unit 102 acquires output information related to the target data based on the analysis result by the data analysis unit 101 (step S2). For example, the related information acquisition unit 102 acquires the related output information from the output information storage unit 106.

[0040] Next, the related information acquisition unit 102 acquires external information related to the target data based on the analysis result by the data analysis unit 101 (step S3). For example, the related information acquisition unit 102 acquires the related external information from the external information storage unit 107.

[0041] Next, the output information generation unit 103 generates output information (draft) using the analysis result by the data analysis unit 101, the output information and external information acquired by the related information acquisition unit 102, and the learning model (step S4). Specifically, the output information generation unit 103 inputs the analysis result, the related information, and the external information into the learning model. As a result, the output information generation unit 103 acquires the output information (draft) from the learning model.

[0042] Next, the output unit 104 outputs the output information (draft) generated by the output information generation unit 103 (step S5). For example, the output unit 104 outputs the output information (draft) to a display unit (not shown) such as a display device for display. At this time, the output unit 104 may output the output information (draft) to a storage unit (not shown) of the information processing device 100 or an external device for storage.

[0043] Next, an input operation by the user is accepted (Y in step S6), and if the input operation is a correction operation (Y in step S7), the output information generation unit 103 corrects the output information (draft) based on the correction operation (step S8).

[0044] Furthermore, when an input operation by the user is accepted (Y in step S6) and the input operation is a confirmation operation (Y in step S9), the output information generation unit 103 confirms the output information based on the confirmation operation. That is, the output information generation unit 103 sets the output information (draft) as the output information (confirmed). Next, the output unit 104 stores the output information (confirmed) in the output information storage unit 106 (step S10). At this time, the output unit 104 may output the output information (confirmed) to a display unit (not shown) such as a display device for display.

[0045] Thereafter, the learning unit 105 re-learns the learning model using the analysis result of the target data, the related information of the target data (output information and external information), and the output information (confirmed) as correct answer data (step S11).

[0046] 2 does not limit the operation of the information processing device 100 of the present disclosure. For example, the process of step S2 and the process of step S3 may be executed in the reverse order or in parallel. Furthermore, for example, the process of step S11 may be executed at any timing after the process of step S10, rather than immediately after the process of step S10.

[0047] In this embodiment, the data analysis unit 101 analyzes target data. The related information acquisition unit 102 acquires output information and external information related to the target data. The output information generation unit 103 generates output information using a learning model that has been trained by machine learning to determine the relationship between the analysis results of the target data, the related information, and the output information including knowledge obtained based on the target data, as well as the analysis results of the target data and the output information and external information related to the target data. This configuration significantly reduces the effort required for users to extract knowledge that meets their needs from the analysis results of the target data and the related information. As a result, vast amounts of data can be effectively utilized, allowing users to efficiently obtain useful information they need.

[0048] Next, an overview of the operation of the information processing device 100 will be described. Fig. 3 is an explanatory diagram illustrating an example of the overview of the operation of the information processing device 100. Note that Fig. 3 is an explanatory diagram for facilitating understanding of the overview of the information processing device 100. Therefore, the operation of the information processing device 100 is not limited to that shown in Fig. 3. Also, the arrows in Fig. 3 simply indicate the direction of signal (data) flow, but do not exclude bidirectionality.

[0049] FIG. 3 illustrates an example of an overview of the application of the information processing device 100 to a disaster prevention system for river flooding. This disaster prevention system collects satellite image data of monitored rivers captured by artificial satellites. One example of data analysis work performed by a user is grasping the situation during a disaster using the collected satellite image data. In the data analysis work, damage status is investigated using information from social media, news, etc. in addition to satellite image data.

[0050] The information processing device 100 shown in Fig. 3 generates, as output information, report data including knowledge (e.g., damage status) obtained based on satellite image data. Note that, in Fig. 3, the output unit 104, output information storage unit 106, external information storage unit 107, and model storage unit 108 of the information processing device 100 are not shown for the sake of simplicity.

[0051] The data analysis unit 101 of the information processing device 100 inputs satellite image data as target data and performs data analysis processing. The data analysis unit 101 can apply a change detection method for analyzing satellite image data by comparing new satellite image data of the same location with past satellite image data. In this case, the content of the data analysis result is the change extraction result obtained by comparing the input satellite image data with the input satellite image and past satellite image data of the same area. The change extraction result includes, for example, data in which an image ID (identifier), the image capture time, and the latitude and longitude of the changed area are associated. Each pixel of the satellite image can be associated with latitude and longitude. Therefore, the data analysis unit 101 can identify the latitude and longitude from pixels determined to have a change.

[0052] The related information acquisition unit 102 acquires report data related to the satellite image data as output information related to the target data. The related report data is past report data related to the satellite image data input as the target data. For example, the related information acquisition unit 102 acquires past report data related to an area captured by an artificial satellite from the output information storage unit 106 based on location information of the area.

[0053] The related information acquisition unit 102 acquires information from a domain different from that of the satellite image data (in other words, from a different information source or acquisition route) as external information related to the target data. For example, the related information acquisition unit 102 acquires the latest external information about a region based on location information of the region imaged by an artificial satellite from the external information storage unit 107. The external information includes, for example, public information about the region provided by public institutions, news reported by news organizations, weather forecasts, and posts on websites such as social networking sites.

[0054] The output information generation unit 103 inputs the change extraction results as the data analysis results. Also, the output information generation unit 103 inputs past report data acquired by the related information acquisition unit 102 as output information related to the target data. Also, the output information generation unit 103 inputs external information acquired by the related information acquisition unit 102 as external information related to the target data.

[0055] The output information generation unit 103 receives a trained learning model as input. The learning model is a machine learning model trained by the learning unit 105 using the analysis results of the satellite image data, related report data, related external information, and report data (confirmed) as correct answer data.

[0056] The output information generation unit 103 generates report data (draft) as output information using the analysis results of the satellite image data, report data related to the satellite image data, external information related to the satellite image data, and the learning model. The report data (draft) includes information (intelligence) indicating findings obtained from the analysis results of the satellite image data and related information. The information (intelligence) included in the report data (draft) is expressed in natural language that is easy for users to understand. The information (intelligence) includes, for example, information indicating the damage situation caused by river flooding and information indicating an action plan for dealing with the damage.

[0057] The user can modify or confirm the report data (draft). When the user confirms the report data (draft), the report data (draft) is stored in a storage unit (e.g., the output information storage unit 106) as report data (confirmed). If the learning model is to be continuously learned even after the information processing device 100 has started operating, this report data (confirmed) is used as the correct answer data.

[0058] The information that users need is not simply information obtained by analyzing target data, but information that can be read from it. The information processing device 100 creates report data that expresses in natural language information (intelligence) that indicates knowledge gained from the analysis results of satellite image data and related information. This significantly reduces the effort required for users to extract information (intelligence) that indicates knowledge that meets their needs from the analysis results of satellite image data and related information. As a result, vast amounts of data can be effectively utilized, allowing users to efficiently obtain the useful information they need.

[0059] Figure 3 shows an example in which the target data to be analyzed is satellite image data. However, the target data may also be image data of the river being monitored taken by a drone, or a combination of these. The target data may also be video data, audio data, or log data.

[0060] The information processing device 100 is not limited to the application example shown in FIG. 3 and can also be applied to other systems. For example, the information processing device 100 can input log data, such as a system log or a security log, of a specific system as target data. In this case, for example, the related information acquisition unit 102 of the information processing device 100 may acquire security information provided by a Computer Security Incident Response Team (CSIRT) as external information based on the analysis results of the log data. The output information generation unit 103 generates, as output information, report data including knowledge obtained based on the log data. The report data includes, for example, information indicating the occurrence status of an abnormality, information indicating whether immediate action is required, and information indicating an action plan for dealing with the abnormality, etc.

[0061] The output information generation unit 103 may generate output information including commands that reflect knowledge obtained based on the log data, instead of or in addition to the report data. The commands that reflect the knowledge are, for example, command statements that cause a specific system or computer to execute a specific process (for example, a process for dealing with an abnormality, etc.). With this configuration, the user can execute an action plan for dealing with an abnormality, etc., by executing the commands included in the output information.

[0062] 4 is a block diagram illustrating the configuration of a computer according to the present disclosure. A CPU 1000 executes processing in accordance with an information processing program stored in a storage device 1001, thereby realizing each function of the information processing device 100 in the above embodiment.

[0063] That is, the CPU 1000 executes processing in accordance with the information processing program stored in the memory device 1001, thereby realizing the functions of the data analysis unit 101, related information acquisition unit 102, output information generation unit 103, output unit 104 and learning unit 105 of the information processing device 100 shown in Figure 1.

[0064] The storage device 1001 is, for example, a non-transitory computer-readable medium. The non-transitory computer-readable medium includes various types of tangible storage media. Specific examples of the non-transitory computer-readable medium include semiconductor memory (e.g., mask ROM, PROM (Programmable ROM), EPROM (Erasable PROM), and flash ROM).

[0065] The memory 1002 is realized by, for example, a RAM (Random Access Memory), and is a storage means for temporarily storing data when the CPU 1000 executes processing.

[0066] Next, an overview of the present disclosure will be described. FIG. 5 is a block diagram illustrating the main components of an information processing device. The information processing device 10 (e.g., corresponding to the information processing device 100) shown in FIG. 5 includes a learning model (e.g., corresponding to the learning model in the embodiment) that learns the relationship between the analysis results of target data and related information and output information including knowledge obtained based on the target data through machine learning; output information generation means 11 (e.g., realized by the output information generation unit 103 in the embodiment) that generates output information (e.g., report data) using the analysis results of the target data (e.g., corresponding to the analysis results of image data), output information related to the target data (e.g., report data generated in the past), and external information (e.g., information from a source different from the image data); and output means 12 (e.g., realized by the output unit 104 in the embodiment) that outputs the output information generated by the output information generation means 11. This configuration significantly reduces the effort required for a user to extract knowledge that meets their purpose from the analysis results of the target data and related information. As a result, vast amounts of data can be effectively utilized, allowing the user to efficiently obtain useful information they need.

[0067] Although the present disclosure has been described above with reference to the embodiments, the present disclosure is not limited to the above-described embodiments. Various modifications that can be understood by those skilled in the art can be made to the configuration and details of the present disclosure within the scope of the present disclosure. Each embodiment can be combined with other embodiments as appropriate.

[0068] Each drawing is merely an example for describing one or more embodiments. Each drawing may relate not only to one particular embodiment, but also to one or more other embodiments. As will be understood by those skilled in the art, various features or steps described with reference to any one drawing can be combined with features or steps shown in one or more other drawings to create, for example, an embodiment not explicitly shown or described. Not all features or steps shown in any one drawing are necessary to describe an exemplary embodiment, and some features or steps may be omitted. The order of steps described in any drawing may be changed as appropriate.

[0069] A part or all of the above-described embodiments can be described as, but not limited to, the following supplementary notes.

[0070] (Appendix 1) An information processing device characterized by comprising: a learning model that learns through machine learning the relationship between the analysis results of target data and related information and output information including knowledge obtained based on the target data; an output information generation means that generates output information using the analysis results of the target data, the output information related to the target data, and external information; and an output means that outputs the output information generated by the output information generation means.

[0071] (Supplementary Note 2) The information processing device according to Supplementary Note 1, comprising: a data analysis means for analyzing target data; and a related information acquisition means for acquiring output information and external information related to the target data based on the analysis result of the target data.

[0072] (Supplementary Note 3) The information processing device according to Supplementary Note 1 or Supplementary Note 2, wherein the output information generating means generates, as output information, report data including findings obtained based on the target data.

[0073] (Supplementary Note 4) The information processing device according to any one of Supplementary Note 1 to Supplementary Note 3, wherein the output information generating means generates output information including a command that reflects knowledge obtained based on the target data.

[0074] (Supplementary Note 5) An information processing device according to any one of Supplementary Notes 1 to 4, wherein the output information generating means uses output information generated based on the analysis results of data related to the target data as output information related to the target data.

[0075] (Supplementary Note 6) The information processing device according to any one of Supplementary Note 1 to Supplementary Note 5, wherein the output information generating means uses information from an information source different from that of the target data as the external information related to the target data.

[0076] (Supplementary Note 7) The information processing device according to any one of Supplementary Note 1 to Supplementary Note 6, wherein the output information generating means confirms the output information based on a confirmation operation by the user.

[0077] (Supplementary Note 8) An information processing device according to Supplementary Note 7, comprising a learning means for learning a learning model using the analysis results of the target data, output information and external information related to the target data, and the determined output information.

[0078] (Appendix 9) An information processing method characterized in that a computer generates output information using a learning model that has learned through machine learning the relationship between the analysis results of target data and related information and output information including knowledge obtained based on the target data, the analysis results of the target data, and output information and external information related to the target data, and outputs the generated output information.

[0079] (Appendix 10) An information processing program for causing a computer to execute an output information generation process that generates output information using a learning model that has learned through machine learning the relationship between the analysis results of target data and related information and output information including knowledge obtained based on the target data, the analysis results of the target data, and output information and external information related to the target data, and an output process that outputs the generated output information.

[0080] Some or all of the elements (e.g., configurations and functions) described in Supplementary Notes 2 to 8 that are dependent on Supplementary Note 1 may also be dependent on Supplementary Notes 9 and 10 in the same dependency relationship as Supplementary Notes 2 to 8. Some or all of the elements described in any Supplementary Note may be applied to various hardware, software, recording means for recording software, systems, and methods. [Explanation of symbols]

[0081] 10,100 Information processing equipment 11 Output information generation means 12 Output Method 101 Data Analysis Department 102 Related Information Acquisition Department 103 Output information generation unit 104 Output section 105 Learning Department 106 Output information storage unit 107 External information storage unit 108 Model Memory Unit 1000 CPU 1001 Storage device 1002 memory

Claims

1. a learning model that learns by machine learning the relationship between the analysis results of the target data, related information, and output information including knowledge obtained based on the target data; and output information generation means that generates output information using the analysis results of the target data, the output information related to the target data, and external information; an output unit that outputs the output information generated by the output information generation unit; 1. An information processing device comprising:

2. data analysis means for analyzing target data; and related information acquisition means for acquiring output information and external information related to the target data based on the analysis result of the target data.

2. The information processing device according to claim 1.

3. The output information generating means generates, as output information, report data including findings obtained based on the target data.

3. The information processing device according to claim 1.

4. The output information generating means generates output information including a command that reflects knowledge obtained based on the target data.

3. The information processing device according to claim 1.

5. The output information generating means uses output information generated based on an analysis result of data related to the target data as output information related to the target data.

3. The information processing device according to claim 1.

6. The output information generating means uses information from a source different from that of the target data as external information related to the target data.

3. The information processing device according to claim 1.

7. The output information generating means determines the output information based on a determination operation by the user.

3. The information processing device according to claim 1.

8. The system includes a learning means for learning the learning model using the analysis results of the target data, output information and external information related to the target data, and the determined output information.

8. The information processing device according to claim 7.

9. The computer generating output information using a learning model that has been trained by machine learning to determine the relationship between the analysis results of the target data, related information, and output information including knowledge obtained based on the target data, and using the analysis results of the target data, and the output information and external information related to the target data; Print the generated output information 1. An information processing method comprising:

10. On the computer, an output information generation process that generates output information using a learning model that has been learned by machine learning the relationship between the analysis results of the target data, related information, and output information including knowledge obtained based on the target data, and the analysis results of the target data, and output information and external information related to the target data; An output process that outputs the generated output information. An information processing program for executing the above.

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