Information processing device, information processing method, and program

Abstract

To enable comparison and review of any documents without relying on pre-prepared templates or check rules. [Solution] The difference extraction unit 51 acquires the document to be evaluated from the user terminal 3. The difference extraction unit 51 extracts differences by comparing the document to be evaluated with the document to be compared, and outputs information indicating those differences as difference information. The evaluation result generation unit 53 works in cooperation with AI 2 to perform an evaluation based on the difference information. The evaluation result generation unit 53 uses a predetermined algorithm to evaluate the appropriateness of the document to be evaluated based on the difference information, and generates information indicating the evaluation result as evaluation result information.

Description

Technical Field

[0001] The present invention relates to an information processing apparatus, an information processing method, and a program.

Background Art

[0002] As a technology related to conventional contract review, each service vendor prepared a prototype in advance and performed a review by comparing it with those prototypes (see, for example, Patent Document 1).

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] However, the conventional contract review technology has the following problems. First, since it can only check against the pattern of the prototype clauses prepared in advance by the service vendor, the review is not effective for clauses not in the prototype or contracts with new transaction forms. Second, since only the pre-prepared check rules and sample revised texts can be displayed, flexible evaluation and improvement proposals according to the content and situation of individual contracts cannot be made. Third, even when the user uses a unique prototype, manual setting work is required, which is time-consuming, and the limitation that it can only be checked against the pre-set pattern remains unchanged. For this reason, it is difficult to perform a practical and dynamic review of various contracts in the prior art.

[0005] The present invention has been made in view of such a situation, and an object thereof is to enable a review by comparing arbitrary documents without depending on pre-prepared prototypes or check rules.

Means for Solving the Problems

[0006] To achieve the above objective, an information processing apparatus according to one aspect of the present invention is: A difference extraction means that extracts differences by comparing the document to be evaluated with an arbitrary comparison document and outputs information indicating those differences as difference information, An evaluation result generation means that evaluates the appropriateness of the document to be evaluated using a predetermined algorithm based on the differential information and generates information indicating the evaluation result as evaluation result information, It is equipped with.

[0007] Each of the information processing method and program according to one aspect of the present invention corresponds to each of the information processing apparatus according to one aspect of the present invention. [Effects of the Invention]

[0008] According to the present invention, it is possible to dynamically review any documents by comparing them and using the difference information, without relying on pre-prepared templates or check rules. [Brief explanation of the drawing]

[0009] [Figure 1] This figure shows an overview of the service that can be realized by an information processing system to which a server according to one embodiment of the information processing device of the present invention is applied. [Figure 2] This figure shows an example of the configuration of an information processing system to which a server according to one embodiment of the information processing device of the present invention is applied. [Figure 3] Figure 2 is a block diagram showing an example of the server hardware configuration in the information processing system. [Figure 4] This is a functional block diagram showing an example of the functional configuration of the server in Figure 3 that constitutes the information processing system in Figure 2. [Figure 5] This figure shows an example of a method for selecting comparison clauses in the information processing device of the present invention (automatic recommendation of similar documents). [Figure 6]This figure shows an example of a method for selecting a comparison clause in the information processing device of the present invention (by document file name or full-text search). [Figure 7] This figure shows an example of a method for selecting a comparison clause in the information processing device of the present invention (document upload). [Figure 8] This figure shows an example of a method for selecting comparison clauses in the information processing device of the present invention (automatic recommendation of similar clauses). [Figure 9] This figure shows an example of a method for selecting a comparative article in the information processing device of the present invention (full-text search of articles). [Figure 10] This figure shows an example of comparing a clause in a document under review with multiple clauses in a comparison document using the information processing device of the present invention. [Figure 11] This figure shows an example of inputting and automatically suggesting positions on a document to be reviewed in the information processing device of the present invention. [Figure 12] This figure shows an example of how to input and specify matters to be considered during review in the information processing device of the present invention. [Figure 13] This figure shows an example of how review results are displayed in the information processing device of the present invention (when a comparison document is selected as shown in Figures 5, 6, and 7). [Figure 14] This figure shows an example of how review results are displayed in the information processing device of the present invention (when the comparison target is selected as a document, as shown in Figures 5, 6, and 7). [Figure 15] This figure shows an example of how review results are displayed in the information processing device of the present invention (when the comparison target is selected as a document, as shown in Figures 5, 6, and 7). [Figure 16] This figure shows an example of displaying review results in the information processing device of the present invention (when the comparison target is selected as a clause, as shown in Figures 8 and 9). [Figure 17] This figure shows an example of a screen for inputting instructions for re-reviewing the review results in the information processing device of the present invention. [Figure 18]It is a diagram showing an example in which the text after review correction in the information processing apparatus of the present invention can be reflected in the main text to be reviewed. [Figure 19] It is a diagram showing an example of an automatic comment creation function for the corrected text in the information processing apparatus of the present invention. [Figure 20] It is a diagram showing an example of evaluation and reuse of the review result and the correction comment itself in the information processing apparatus of the present invention. [Figure 21] It is a diagram showing an example of document clustering, patterning, and reuse of the user registration document in the information processing apparatus of the present invention. [Figure 22] It is a diagram showing an example of a flowchart of a solution method in the information processing apparatus of the present invention.

Embodiments of the Invention

[0010] <于 Hereinafter, embodiments of the present invention will be described with reference to the drawings.

[0011] First, referring to FIG. 1, an overview of a service (hereinafter referred to as "this service") that can be realized by an information processing system (see FIG. 2 described later) to which a server according to an embodiment of the information processing apparatus of the present invention is applied will be described. FIG. 1 is a diagram showing an overview of this service that can be realized by an information processing system to which a server according to an embodiment of the information processing apparatus of the present invention is applied.

[0012] This service is a service that performs a review dynamically (for example, in real time) from difference information by comparing arbitrary documents.

[0013] Specifically, for example, in FIG. 1, user A inputs an evaluation target document to server 1 through user terminal 3, server 1 automatically acquires a comparison target document, compares the evaluation target document with the comparison target document, and extracts differences (step S1). Then, server 1 performs an appropriateness evaluation based on the difference information (step S2) and outputs evaluation result information B to the user (step S3), and a series of processing flows are shown.

[0014] In step S1 of Figure 1, as described above, user A inputs the document to be evaluated into server 1 via user terminal 3. Server 1 acquires the document to be evaluated from user terminal 3 and, in cooperation with AI 2, automatically acquires the document to be compared. Server 1 compares the document to be evaluated and the document to be compared and extracts the differences. In step S2, Server 1 collaborates with AI 2 to perform an appropriateness assessment based on differential information. During this process, Server 1 performs tasks such as documenting risk points, considering positional information, and generating proposed revisions. In step S3, Server 1 outputs evaluation result information B to User A. Server 1 provides a re-evaluation function as needed. This overcomes the limitation of being able to review documents only using conventional templates, and enables appropriateness assessment between arbitrary documents.

[0015] In step S1, this service enables the automatic acquisition of comparison documents. Server 1 collaborates with AI 2 to automatically retrieve comparison documents through automated recommendation of similar documents and full-text search functionality. This overcomes the limitations of being restricted to pre-defined template clauses and enables a flexible document evaluation workflow based on diverse comparison criteria.

[0016] In step S1, this service enables precise comparison at the partial information unit level. Server 1 works in cooperation with AI 2 to extract partial information units from the document to be evaluated (for example, the validity period in Article 5 of the outsourcing contract) and compare them with partial information units from the document to be compared. This makes it possible to precisely extract local differences that are difficult to detect through a comprehensive comparison of the entire document, enabling a more detailed assessment of its suitability.

[0017] In step S2, this service enables the output of evaluation results through the dynamic generation of risk point texts. Server 1 works in cooperation with AI 2 to analyze risk points from the differential information extracted in step S1 and generates evaluation result information that includes written information about those risk points (for example, "The description of the contract period is ambiguous, and there is a risk that it will become an indefinite contract"). This overcomes the limitation of only being able to display pre-prepared check results and sample revised texts, and enables the provision of dynamic risk analysis results tailored to individual differences.

[0018] In Step S2, this service enables appropriateness assessment that takes positional information into consideration. Server 1 collaborates with AI 2 to acquire positional information (such as whether it is the client or the contractor) in the document to be evaluated, and performs an appropriateness assessment taking this positional information into consideration. For example, from the client's perspective, they might conduct a risk analysis specific to their position, such as "Are the reporting obligations excessive?" or from the contractor's perspective, "Are the rights to the deliverables clearly secured?" This allows for a more appropriate risk assessment tailored to the contracting parties' positions, going beyond simple difference comparisons, and enabling the provision of more practical and useful assessment results.

[0019] In Step S3, this service allows for continuous improvement through a re-evaluation function. Server 1 receives a re-evaluation instruction for the evaluation result information during result generation and output (for example, "Please re-evaluate with greater emphasis on compliance"), and re-executes the evaluation in step S2 based on the re-evaluation instruction. This enables a gradual improvement in evaluation accuracy beyond a one-time static evaluation, and allows for flexible evaluation refinement (continuous improvement and precision of evaluation) in response to additional requests from user A.

[0020] In step S2, this service enables the dynamic generation of proposed revisions (e.g., real-time generation). Server 1 collaborates with AI 2 to generate proposed revisions to the document under evaluation based on differential information, and generates evaluation result information that includes these proposed revisions. This overcomes the limitation of only being able to display pre-prepared sample revisions, enabling the dynamic generation of specific improvement proposals tailored to individual differences.

[0021] In step S3, this service allows for the automatic incorporation of revised proposals into the document. Server 1 can reflect the proposed revisions included in the evaluation result information into the document being evaluated during result generation and output. Server 1 has the functionality to insert the revised clauses as change history in a Word file or to overwrite them as plain text. This goes beyond simply displaying evaluation results, enabling a consistent workflow from evaluation to revision, and significantly improving the efficiency of document improvement work.

[0022] Next, with reference to Figure 2, we will describe the configuration of an information processing system to which an information processing system that realizes the provision of the above-mentioned service, namely an information processing system to which a server according to one embodiment of the information processing device of the present invention is applied. Figure 2 shows an example of the configuration of an information processing system to which a server according to one embodiment of the information processing device of the present invention is applied.

[0023] The information processing system shown in Figure 2 is configured to include Server 1, AI 2, and user terminals 3-1 to 3-n. Server 1, AI 2, and user terminals 3-1 to 3-n are interconnected via a network N such as the Internet. Furthermore, if there is no need to distinguish between user terminals 3-1 through 3-n individually, they will be collectively referred to as "user terminal 3".

[0024] Server 1 is an information processing device managed by the service provider of this service (Figure 1). Server 1 performs various processes necessary to realize this service while communicating with AI 2 and user terminal 3 as needed.

[0025] AI2 refers to generative AI and the like, provided by an external service. User terminals 3-1 to 3-n are information processing devices operated by the user, and consist of smartphones, tablets, personal computers, etc.

[0026] Figure 3 is a block diagram showing an example of the server hardware configuration in the information processing system shown in Figure 2.

[0027] Server 1 comprises a CPU (Central Processing Unit) 11, ROM (Read Only Memory) 12, RAM (Random Access Memory) 13, a bus 14, an input / output interface 15, an input unit 16, an output unit 17, a storage unit 18, a communication unit 19, and a drive 20.

[0028] The CPU 11 executes various processes according to the program recorded in the ROM 12 or the program loaded from the storage unit 18 into the RAM 13. RAM13 also stores data and other information necessary for the CPU11 to perform various processes.

[0029] The CPU 11, ROM 12, and RAM 13 are interconnected via a bus 14. An input / output interface 15 is also connected to this bus 14. The input / output interface 15 is connected to an input unit 16, an output unit 17, a storage unit 18, a communication unit 19, and a drive 20.

[0030] The input unit 16 is configured, for example, with a keyboard, and is used to input various types of information. The output unit 17 consists of a display such as an LCD and a speaker, and outputs various information as images and sounds. The memory unit 18 is composed of DRAM (Dynamic Random Access Memory) and stores various types of data. The communication unit 19 communicates with other devices via a network N, including the Internet.

[0031] A removable media 30, such as a magnetic disk, optical disk, magneto-optical disk, or semiconductor memory, is appropriately mounted in the drive 20. Programs read from the removable media 30 by the drive 20 are installed in the storage unit 18 as needed. Furthermore, the removable media 30 can store various types of data stored in the storage unit 18, just as the storage unit 18 does.

[0032] Although not shown in the diagram, user terminal 3 can also have a hardware configuration that is basically the same as that shown in Figure 3. Therefore, the explanation of the hardware configuration of user terminal 3 will be omitted.

[0033] Through the cooperation of various hardware and software components that make up the information processing system in Figure 2, including Server 1 in Figure 3, various processes for providing the service in Figure 1 can be executed.

[0034] Figure 4 is a functional block diagram showing an example of the functional configuration of the server in Figure 3 within the information processing system shown in Figure 2.

[0035] As shown in Figure 4, the CPU 11 of server 1 functions as follows: difference extraction unit 51, document acquisition unit 52, evaluation result generation unit 53, re-evaluation unit 54, and reflection processing unit 55. One area of ​​the storage unit 18 of server 1 is provided with a document information DB 71, an evaluation result DB 72, and a position information DB 73. By coordinating these functional units and databases, a comprehensive document review system, as shown in Figure 1, from steps S1 to S3, is realized. The difference extraction unit 51 and the evaluation result generation unit 53 work in cooperation with AI2 to perform processing in steps S1 and S2 of Figure 1.

[0036] The difference extraction unit 51 performs the difference extraction process in step S1 of Figure 1. The difference extraction unit 51 acquires the document to be evaluated from the user terminal 3. The difference extraction unit 51 works in cooperation with AI 2 to automatically acquire the document to be compared. The difference extraction unit 51 extracts differences by comparing the document to be evaluated with the document to be compared, and outputs information indicating those differences as difference information. The difference extraction unit 51 stores the extracted difference information in the evaluation result DB 72.

[0037] The difference extraction unit 51 extracts partial information units from the document to be evaluated and the document to be compared and performs a comparison. For example, it extracts the clause of Article 5 (Term of Validity) of the outsourcing contract as a partial information unit and compares it in detail with the corresponding clause in the document to be compared. The difference extraction unit 51 can also perform a 1:N comparison between a single review target clause and multiple comparison target clauses. The difference extraction unit 51 enables precise extraction of local differences that are difficult to find through a batch comparison of the entire document.

[0038] The document acquisition unit 52 supports the automatic acquisition function of comparison target documents in step S1 of Figure 1. The document acquisition unit 52 works in cooperation with AI2 to automatically acquire comparison target documents. The document acquisition unit 52 searches for and acquires appropriate comparison target documents from the document information DB 71 using its automatic similar document recommendation function. The document retrieval unit 52 identifies relevant documents based on keywords using its full-text search function. The document retrieval unit 52 automatically identifies different versions of the same document (for example, the 2023 and 2024 versions of the outsourcing contract) and proposes them as comparison targets. The document acquisition unit 52 can also compare the data with a playbook (a list of the company's decision criteria). The document acquisition unit 52 also accepts document uploads from users (docx files, pdf files, etc.).

[0039] The document acquisition unit 52 can perform similar searches and similarity searches not only on data uploaded to web services on the cloud, but also on files on the local computer. Specifically, when a contract is opened in a Word file, it has a function to automatically search for similar Word files or PDF files on the computer and present them as comparison targets. This enables a review process that efficiently utilizes the existing document assets available to User A. The document acquisition unit 52 overcomes the conventional limitation of being limited to pre-prepared template clause patterns, enabling a flexible and efficient document evaluation workflow based on diverse comparison criteria.

[0040] The evaluation result generation unit 53 executes the suitability evaluation process in step S2 of Figure 1. The evaluation result generation unit 53 works in cooperation with AI2 to perform an evaluation based on differential information. Based on the differential information, the evaluation result generation unit 53 uses a predetermined algorithm to evaluate the appropriateness of the document to be evaluated and generates information indicating the evaluation result as evaluation result information. The evaluation result generation unit 53 analyzes risk points from the differential information and generates evaluation result information that includes information describing those risk points in text. For example, it automatically generates text describing a risk point such as, "The description of the contract period is ambiguous, and there is a risk that it will become an indefinite contract."

[0041] The evaluation result generation unit 53 obtains position information (client, contractor, etc.) from the position information DB 73 in the document to be evaluated, and generates evaluation result information taking this position information into consideration. The evaluation result generation unit 53 performs position-specific risk analysis, such as "excessive reporting obligations" from the client's perspective, or "unclear rights to deliverables" from the contractor's perspective. The evaluation result generation unit 53 generates proposed revisions to the document under evaluation based on the difference information and generates evaluation result information including the proposed revisions. The evaluation result generation unit 53 generates comprehensive evaluation results including "difference summary," "risk points," and "revised clauses," and also provides identification representations based on importance (degree of risk).

[0042] The evaluation result generation unit 53 overcomes the limitation that only pre-prepared check results and revised drafts can be displayed, and enables the provision of dynamic risk analysis results and improvement proposals tailored to individual differences.

[0043] The re-evaluation unit 54 performs the re-evaluation function in step S3 of Figure 1. The re-evaluation unit 54 receives instructions for re-evaluation of the evaluation result information. The re-evaluation unit 54 also receives additional instructions from the user, such as "Please re-evaluate with greater emphasis on compliance" or "Please re-analyze focusing on legal risks." The re-evaluation unit 54 re-executes the evaluation by the evaluation result generation unit 53 based on the re-evaluation instruction. The re-evaluation unit 54 stores the re-evaluation results in the evaluation result DB 72 and accumulates them as evaluation history. The re-evaluation unit 54 enables a gradual improvement in evaluation accuracy beyond a one-time static evaluation, and allows for flexible evaluation refinement (continuous improvement and precision of evaluation) in response to additional requests from user A.

[0044] The reflection processing unit 55 executes the revised proposal reflection function in step S3 of Figure 1. The reflection processing unit 55 reflects the proposed revisions included in the evaluation result information into the document under evaluation. The reflection processing unit 55 has a function to insert the revised clauses, for example, as change history in a Word file. The reflection processing unit 55 also has a function to overwrite the proposed revisions as plain text. The reflection processing unit 55 highlights the modified areas and automatically adds comments explaining the reasons for the modifications. The reflection processing unit 55 automatically generates comments explaining the modifications, saving the effort of manually creating explanatory texts for the reasons for the modifications. The reflection processing unit 55 completes a consistent workflow from evaluation to correction, significantly improving the efficiency of document improvement work.

[0045] Next, specific embodiments of the present invention will be described with reference to Figure 5 and subsequent figures. Figures 5 to 21 are example diagrams illustrating specific operational examples of each functional block shown in Figure 4 and the processing steps S1 to S3 shown in Figure 1.

[0046] Figure 5 shows an example of a method for selecting comparison clauses in the information processing device of the present invention (automatic recommendation of similar documents).

[0047] The document acquisition unit 52, as part of the automatic acquisition process of comparison target documents in step S1 of Figure 1, automatically recommends the documents to be reviewed (the documents to be compared), as shown in Figure 5. It is also possible to compare different versions of the same document. Furthermore, it is possible to compare against a playbook (a list of the company's judgment criteria) instead of comparing against a document. The document acquisition unit 52 reduces the burden of prior preparation, which previously required the creation of templates, and enables an efficient document evaluation workflow.

[0048] Furthermore, the document acquisition unit 52 can perform the same search and similarity search (local file search function) not only on data uploaded to web services on the cloud, but also on files on the local computer. Specifically, when a contract is opened in a Word file, it has a function that automatically searches for similar Word or PDF files on the computer and presents them as comparison points. This enables efficient review using existing document assets available to User A. This feature allows for the automatic acquisition of comparison documents in step S1 of Figure 1 to be performed from a wider variety of document sources.

[0049] Figure 6 shows an example of a method for selecting a comparison clause in the information processing device of the present invention (by document file name or full-text search).

[0050] As part of the automatic acquisition process of comparison target documents in step S1 of Figure 1, the document acquisition unit 52 can search for the comparison target document by full-text search, as shown in Figure 6. This search function encompasses both a search function for documents stored in a cloud database and the aforementioned local file search function. This allows the document acquisition unit 52 to efficiently acquire appropriate comparison documents from the document information DB 71. These search results are then subjected to comparison processing by the difference extraction unit 51 in step S1 of Figure 1.

[0051] Figure 7 shows an example of a method for selecting a comparison clause in the information processing device of the present invention (document upload).

[0052] The document acquisition unit 52 can acquire the comparison target document by uploading the comparison target document, as shown in Figure 7, as part of the comparison target document acquisition process in step S1 of Figure 1. Supported file formats include, but are not limited to, docx, doc, rtf, and pdf files. By ensuring the extensibility of supported file formats, it is possible to support a wide variety of document formats. As a result, the document acquisition unit 52 can use a document arbitrarily specified by the user as the comparison target, and provides it as input for the difference extraction process in step S1 of Figure 1.

[0053] Figure 8 shows an example of a method for selecting comparison clauses in the information processing device of the present invention (automatic recommendation of similar clauses).

[0054] As shown in Figure 8, the document acquisition unit 52 can automatically recommend articles similar to the article under review (articles to be compared) as part of the partial information unit acquisition process of the comparison target document in step S1 of Figure 1. This function enables similarity determination not only at the overall document level but also at the article level. As a result, the difference extraction unit 51 extracts and compares partial information units, thereby enabling the extraction of local differences that would be difficult to find through a comprehensive comparison of the entire document. This process embodies the difference extraction of partial information units in step S1 of Figure 1.

[0055] Figure 9 shows an example of a method for selecting articles to be compared in the information processing device of the present invention (full-text search of articles). As part of the process of acquiring comparison targets in partial information units in step S1 of Figure 1, the document acquisition unit 52 can search for the comparison target article by full-text search, as shown in Figure 9. This article-level search makes it possible to compare only specific articles rather than the entire document. This allows the difference extraction unit 51 to compare any portion of the document under review (including the entire document) with the clauses of one or more arbitrary documents. This function supports difference extraction at the partial information unit level in step S1 of Figure 1.

[0056] Figure 10 shows an example of comparing a clause in a document under review with multiple clauses in a comparison document using the information processing device of the present invention.

[0057] In the difference extraction process in step S1 of Figure 1, the difference extraction unit 51 can also perform a 1:N comparison (and vice versa) when there are multiple similar clauses in the document being compared, as shown in Figure 10. This many-to-many comparison function makes it possible to discover complex risks and opportunities that might be overlooked in a simple one-to-one clause comparison. This enables more comprehensive difference extraction. The results of this processing are provided to the evaluation result generation unit 53 in step S2 of Figure 1 for appropriateness evaluation.

[0058] Figure 11 shows an example of the information processing device of the present invention that inputs and automatically suggests positions on documents to be reviewed.

[0059] The evaluation result generation unit 53, as part of the appropriateness evaluation process that takes into account the position information in step S2 of Figure 1, allows you to specify which position perspective to review by inputting the position on the document before the review, as shown in Figure 11. Candidate suggestions such as "Party A (Company XX)" and "Party B (Company YY)" are presented. The system automatically extracts the positions described in the document and matches them with the names of the companies, individuals, and other parties involved, and presents the results as automatic suggestions for position input (you are not required to follow the suggestions). Furthermore, the evaluation result generation unit 53 has a function to automatically determine if the positions of the review target document and the comparison target document are reversed. For example, if the position of the client is that of the company in the review target document, but the position is set to that of Party B in the comparison target document, the unit automatically detects this reversal, performs an appropriate position correction, and then performs the review. The position information is stored in the position information DB 73, enabling an appropriate risk assessment according to the position in step S2 of Figure 1.

[0060] Figure 12 shows an example of how to input and specify matters to be considered during review in the information processing device of the present invention.

[0061] In the suitability evaluation process in step S2 of Figure 1, the evaluation result generation unit 53 allows input and specification of matters to be considered during the review in predetermined fields, as shown in Figure 12. The evaluation result generation unit 53 has the function of processing supplementary information and comments associated with both the document under review and the document being reviewed. This enables a comprehensive review that considers not only the document text but also, for example, past negotiation history, reasons for revisions, and comments from stakeholders. This process enables a more multifaceted assessment of appropriateness based on differential information in step S2 of Figure 1.

[0062] Figures 13, 14, and 15 show examples of review result display in the information processing device of the present invention. These represent the output processing of evaluation result information in step S3 of Figure 1.

[0063] As shown in Figure 13, the evaluation result generation unit 53 displays the results of an automated review by comparing corresponding clauses in the document being reviewed and the document being compared. "Difference Summary," "Risk Points," and "Revised Clauses" are examples of review results, and it is acceptable to display only a portion of these. For example, it is acceptable to display only "Risk Points," or to display both "Risk Points" and "Revised Clauses." Furthermore, one or more options can be presented for each item. The importance (risk level, etc.) can be identified and expressed from the review results. The documents reviewed and compared may be one or more. This display process enables the output of evaluation result information B in step S3 of Figure 1.

[0064] As shown in Figure 14, the evaluation result generation unit 53 displays the automatic review results even for clauses of a type that exist only in the document being reviewed. The evaluation result generation unit 53 checks the risk associated with the presence of this clause. The differences between the clause under review and the "revised clause" which is the result of the review can be highlighted. This process is part of step S3, which outputs the evaluation result information generated in step S2 of Figure 1 in a format that is easy for the user to understand.

[0065] As shown in Figure 15, the evaluation result generation unit 53 displays automated review results even for clause types that exist only in the comparison document. The evaluation result generation unit 53 checks for the risks associated with the absence of this clause. This process enables the provision of dynamic risk analysis results in step S3 of Figure 1.

[0066] Figure 16 shows an example of the display of review results in the information processing device of the present invention (automatic review results obtained by comparing articles found in similarity searches and articles found in full-text searches).

[0067] As shown in Figure 16, the evaluation result generation unit 53 displays the results of an automatic review by comparing the articles found in the similarity search with the articles found in the full-text search. The evaluation result generation unit 53 can highlight the differences between the article under review and the "revised article" which is the review result. The number of articles reviewed and compared can be one or more. This process uses the difference information extracted in step S1 of Figure 1, and the results evaluated in step S2, to output specific improvement proposals in step S3.

[0068] Figure 17 shows an example of a screen in the information processing device of the present invention that allows input of an instruction to re-review the review results.

[0069] The re-evaluation unit 54, as part of its re-evaluation function in step S3 of Figure 1, modifies the review results based on the re-review instructions, as shown in Figure 17. The re-evaluation unit 54 can also perform a re-review by freely describing the re-review instructions. Upon receiving a re-evaluation instruction, the re-evaluation unit 54, in cooperation with the evaluation result generation unit 53, re-executes the evaluation in step S2 and outputs the improved evaluation result in step S3.

[0070] Figure 18 shows an example of how the revised clauses of the information processing device of the present invention can be reflected in the main text of the document being reviewed.

[0071] The reflection processing unit 55, as part of the process of reflecting the proposed revisions in step S3 of Figure 1, can reflect the revised clauses into the main text under review, as shown in Figure 18. The reflection processing unit 55 can overwrite or insert changes, revision history, plain text, etc. This process is completed in step S3 by actually reflecting the evaluation result information, including the proposed revisions generated in step S2 of Figure 1, into the document.

[0072] Figure 19 shows an example of the automatic comment generation function for revised drafts in the information processing device of the present invention.

[0073] As part of the revision proposal generation process in step S2 of Figure 1, the evaluation result generation unit 53 automatically generates comments explaining the revisions, as shown in Figure 19. The evaluation result generation unit 53 can reduce the effort required to manually create explanatory texts for the reasons for the revisions. This process enables the provision of dynamic risk analysis results corresponding to the individual differences in step S3 of Figure 1.

[0074] Figure 20 shows an example of evaluation and reuse of review results and correction comments themselves in the information processing device of the present invention.

[0075] The system shown in Figure 20 allows highly-rated reviews to be prioritized for use in similar reviews in the future. By visualizing highly-rated reviews, review perspectives can be accumulated and used for sharing know-how. The system shown in Figure 20 allows for the persistent storage of review results, processes, and their corresponding evaluation results. The data persistence mechanism enables the persistent storage of review results, processes, and their corresponding evaluation results. This function improves the quality and reuse of the evaluation result information output in step S3 of Figure 1, and contributes to improving the processing accuracy of steps S1 to S3 in the future.

[0076] Furthermore, the system shown in Figure 20 includes both manual and automatic evaluation mechanisms. The system creates a mechanism for manually and automatically evaluating review results and processes. This function enables continuous improvement of the evaluation process using a predetermined algorithm in step S2 of Figure 1.

[0077] Figure 21 shows an example of text clustering, patterning, and reuse of user registration documents in the information processing device of the present invention.

[0078] As shown in Figure 21, this service can create detailed patterns from a group of documents containing the same concept and extract the difference patterns. The appropriate pattern is selected for the review and reflected in the response. Alternatively, a summary of the patterns is presented so that user A can make a selection. The document acquisition unit 52 reduces the burden of preparing templates in advance and realizes an efficient document evaluation workflow. This function supports the automatic acquisition process of comparison documents in step S1 of Figure 1 and contributes to improving the accuracy of the suitability evaluation in step S2.

[0079] Figure 22 is a diagram showing an example flowchart of a solution method in the information processing device of the present invention.

[0080] Figure 22 shows a series of processing steps, including selecting the document to be reviewed (DR), selecting the document to be compared (DC), matching the corresponding clauses in the DR and DC, creating a review request prompt for each matched clause, sending a review request, displaying the review results, creating a re-review request, and inputting and selecting the position of the person being reviewed. This flowchart is a detailed breakdown of the process represented by steps S1 to S3 in Figure 1. In the correspondence with each functional block in Figure 4, the selection of the document to be reviewed (DR) corresponds to the process in which the difference extraction unit 51 receives input from the user terminal 3. The selection of the document to be compared (DC) corresponds to the automatic acquisition process by the document acquisition unit 52. The matching of corresponding clauses between the DR and DC corresponds to the difference extraction process by the difference extraction unit 51. The review request corresponds to the process in which the evaluation result generation unit 53 collaborates with the AI ​​2. The display of the review results corresponds to the generation and output process of evaluation result information by the evaluation result generation unit 53. The creation of a re-review request corresponds to the re-evaluation process by the re-evaluation unit 54. This enables the difference extraction unit 51, document acquisition unit 52, evaluation result generation unit 53, re-evaluation unit 54, and reflection processing unit 55 to work together to realize a comprehensive system that compares arbitrary documents and performs reviews based on the difference information.

[0081] Although one embodiment of the present invention has been described above, the present invention is not limited to the embodiments described above, and any modifications, improvements, etc. that can achieve the objectives of the present invention are considered to be included in the present invention.

[0082] For example, in the above-described embodiment, the difference extraction unit 51 to the reflection processing unit 55 performed processing in cooperation with AI2, but the invention is not limited to this, and processing may be performed in cooperation with AI (including those located within Server 1) not shown, or it may be performed independently based on autonomous judgment without cooperating with AI.

[0083] Furthermore, the system configuration shown in Figure 2 and the hardware configuration of Server 1 shown in Figure 3 are merely illustrative examples for achieving the objectives of the present invention and are not particularly limited.

[0084] Furthermore, the functional block diagram shown in Figure 4 is merely illustrative and not particularly limiting. In other words, it is sufficient that the information processing system in Figure 2 has the functionality to execute the various processes described above as a whole, and the functional blocks and databases used to realize this functionality are not particularly limited to the example in Figure 4.

[0085] Furthermore, the location of the functional blocks and database is not limited to Figure 4 and can be arbitrary. For example, at least a portion of the functional blocks and database located on the server 1 side may be provided on the AI2 side, the user terminal 3 side, or other information processing device not shown.

[0086] Furthermore, the series of processes described above can be executed by hardware or by software. Furthermore, a single functional block may consist of hardware alone, software alone, or a combination of both.

[0087] When a series of processes are executed by software, the programs that make up that software are installed on a computer or other device from a network or storage medium. The computer may be a computer that is built into dedicated hardware. Furthermore, a computer can be any computer capable of performing various functions by installing various programs, such as a server, a general-purpose smartphone, or a personal computer.

[0088] Such recording media containing programs may consist not only of removable media (not shown) distributed separately from the main unit of the device to provide the program to the user, but also of recording media provided to the user in a state where they are pre-installed in the main unit of the device.

[0089] In this specification, the step of describing a program to be recorded on a recording medium includes not only processes that are performed chronologically in that order, but also processes that are not necessarily performed chronologically, but are executed in parallel or individually.

[0090] In summary, the information processing device to which the present invention applies only needs to have the following configuration, and can take various forms. In other words, the information processing device to which the present invention is applied (for example, Server 1 in Figures 1 to 4) is: A difference extraction means (including, for example, the difference extraction process in step S1 of Figure 1, the difference extraction unit 51 in Figure 4, the comparison target document selection function shown in Figures 5 to 9, and the many-to-many comparison function shown in Figure 10) extracts the differences by comparing the document to be evaluated with an arbitrary comparison target document and outputs information indicating those differences as difference information. An evaluation result generation means (including, for example, the appropriateness evaluation process in step S2 of Figure 1, the evaluation result generation unit 53 of Figure 4, the input and automatic suggestion function for position information shown in Figure 11, the input and specification function for review considerations shown in Figure 12, the review result display function shown in Figures 13 to 16, the automatic comment creation function shown in Figure 19, etc.) that evaluates the appropriateness of the document to be evaluated using a predetermined algorithm based on the difference information and generates information indicating the evaluation result as evaluation result information, Having that will suffice.

[0091] In this way, it becomes possible to dynamically review arbitrary documents by comparing them and analyzing the differences, without relying on pre-prepared templates or check rules. This overcomes the conventional limitation of "reviews can only be done using templates," and enables appropriateness evaluation between arbitrary documents.

[0092] Furthermore, the system may also include document acquisition means for automatically acquiring the comparison target documents (for example, the automatic comparison target document acquisition function in step S1 of Figure 1, the document acquisition unit 52 in Figure 4, the automatic similar document recommendation function shown in Figure 5, the file name / full text search function shown in Figure 6, the upload function shown in Figure 7, the automatic similar clause recommendation function shown in Figure 8, the clause full text search function shown in Figure 9, etc.).

[0093] This reduces the burden of prior preparation, which traditionally required the creation of templates, and enables the realization of an efficient document evaluation workflow.

[0094] Furthermore, the difference extraction means can extract and compare partial information units from the document to be evaluated and the document to be compared (including, for example, the comparison process of partial information units in step S1 of Figure 1, the comparison process of partial information units by the difference extraction unit 51 in Figure 4, and the precise comparison function at the clause level shown in Figures 8 to 10).

[0095] This enables the precise extraction of local differences that are difficult to detect through a comprehensive comparison of the entire document, allowing for a more detailed assessment of its suitability.

[0096] Furthermore, the evaluation result generation means can analyze risk points from the difference information and generate evaluation result information that includes information describing the risk points in text form (including the suitability evaluation process in step S2 of Figure 1, the risk analysis and text creation process by the evaluation result generation unit 53 in Figure 4, and the risk point display function shown in Figures 13 to 16).

[0097] This overcomes the conventional limitation of only being able to display pre-prepared check results and revised drafts, and enables the provision of dynamic risk analysis results tailored to individual differences.

[0098] Furthermore, the evaluation result generation means can acquire position information in the document to be evaluated and generate the evaluation result information taking that position information into consideration (for example, the appropriateness evaluation process that takes position information into consideration in step S2 of Figure 1, the position consideration process that utilizes the position information DB 73 by the evaluation result generation unit 53 in Figure 4, the position input and automatic suggestion function shown in Figure 11, etc.).

[0099] This enables "appropriate risk assessment tailored to the contracting parties' positions" beyond simple difference comparisons, allowing for the provision of more practical and useful assessment results.

[0100] Furthermore, the system may further include a re-evaluation means (for example, the re-evaluation function in step S3 of Figure 1, the re-evaluation unit 54 in Figure 4, the re-review instruction input screen function shown in Figure 17, etc.) that receives a re-evaluation instruction for the evaluation result information and re-executes the evaluation by the evaluation result generation means based on the re-evaluation instruction.

[0101] This goes beyond a one-time static evaluation, enabling a "gradual improvement in evaluation accuracy" and flexible evaluation refinement (continuous improvement and precision of evaluation) in response to additional user requests.

[0102] Furthermore, the evaluation result generation means can generate a proposed revision of the document to be evaluated based on the difference information and generate the evaluation result information including the proposed revision (for example, the proposed revision generation process in step S2 of Figure 1, the proposed revision generation process by the evaluation result generation unit 53 in Figure 4, the revised clause display function shown in Figures 13 to 16, the revised text comment automatic creation function shown in Figure 19, etc.).

[0103] This overcomes the conventional limitation of only being able to display pre-prepared sample revised texts, enabling the dynamic generation of specific improvement suggestions tailored to individual differences.

[0104] Furthermore, the system may further include a reflection processing means for reflecting the proposed revisions included in the evaluation result information into the document to be evaluated (for example, the proposed revision reflection function in step S3 of Figure 1, the reflection processing unit 55 in Figure 4, the revised clause text reflection function shown in Figure 18, etc.).

[0105] This goes beyond simply displaying evaluation results, enabling a complete workflow from evaluation to revision, and significantly improving the efficiency of document improvement work. [Explanation of Symbols]

[0106] 1...Server, 2...AI, 3...User terminal, A...User, B...Evaluation results, N...Network, 11...CPU, 12...ROM, 13...RAM, 14...Bus, 15...Input / Output interface, 16...Input unit, 17...Output unit, 18...Storage unit, 19...Communication unit, 20...Drive, 30...Removable media, 51...Difference extraction unit, 52...Document acquisition unit, 53...Evaluation result generation unit, 54...Re-evaluation unit, 55...Reflection processing unit, 71...Document information DB, 72...Evaluation result DB, 73...Position information DB

Claims

1. A difference extraction means that extracts differences by comparing the document to be evaluated with an arbitrary comparison document and outputs information indicating those differences as difference information, An evaluation result generation means that evaluates the appropriateness of the document to be evaluated using a predetermined algorithm based on the differential information and generates information indicating the evaluation result as evaluation result information, An information processing device equipped with the following features.

2. The system further includes a document acquisition means for automatically acquiring the aforementioned comparison target documents. The information processing apparatus according to claim 1.

3. The difference extraction means extracts partial information units from the document to be evaluated and the document to be compared and compares them. The information processing apparatus according to claim 1.

4. The evaluation result generation means analyzes risk points from the difference information and generates evaluation result information that includes information describing the risk points in text form. The information processing apparatus according to claim 1.

5. The evaluation result generation means acquires position information in the document to be evaluated and generates the evaluation result information taking said position information into consideration. The information processing apparatus according to claim 1.

6. The system further includes a re-evaluation means that receives a re-evaluation instruction for the aforementioned evaluation result information and re-executes the evaluation by the evaluation result generation means based on the re-evaluation instruction. The information processing apparatus according to claim 1.

7. The evaluation result generation means generates a proposed revision of the document to be evaluated based on the difference information, and generates the evaluation result information including the proposed revision. The information processing apparatus according to claim 1.

8. The system further includes a reflection processing means for reflecting the proposed revisions included in the evaluation result information into the document being evaluated. The information processing apparatus according to claim 1.

9. An information processing method performed by an information processing device, A difference extraction step that extracts differences by comparing the document to be evaluated with an arbitrary comparison document and outputs information indicating those differences as difference information, An evaluation result generation step in which the appropriateness of the document to be evaluated is evaluated using a predetermined algorithm based on the differential information, and information indicating the evaluation result is generated as evaluation result information, Information processing methods including

10. On the computer, A difference extraction step that extracts differences by comparing the document to be evaluated with an arbitrary comparison document and outputs information indicating those differences as difference information, An evaluation result generation step in which the appropriateness of the document to be evaluated is evaluated using a predetermined algorithm based on the differential information, and information indicating the evaluation result is generated as evaluation result information, A program that executes control processes, including those mentioned above.

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