Processing device, processing program, and processing method

Abstract

To provide a processing device, a processing program, and a processing method that can more efficiently process document information.SOLUTION: A processing device that comprises at least one processor is provided. The at least one processor is configured to perform processing for acquiring input document information, determining whether the acquired document information includes contract information or not, and classifying the acquired document information depending on the determined result.SELECTED DRAWING: Figure 4

Description

[Technical Field]

[0001] The present disclosure relates to a processing device, a processing program, and a processing method configured to process document information. [Background technology]

[0002] Systems for acquiring details written in a contract and reviewing the contract have been proposed. For example, Patent Document 1 describes an information processing system for supporting leasing contracts, comprising: a scoring means for calculating an evaluation score for scoring the creditworthiness of a lease property user based on data on details written in a predetermined lease contract request form prepared in advance and credit information data on the lease property seller related to the lease contract; an evaluation means for evaluating whether the lease contract request satisfies predetermined approval criteria based on the details written in the lease contract request form and the evaluation score calculated by the scoring means; a lease contract approval means for approving the lease contract request if the evaluation means determines that the lease contract request satisfies the approval criteria; and a contract creation means for calculating a lease fee based on the details written in the lease contract request form and automatically creating a lease contract with the lease property user (lease contract holder). [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Japanese Patent Application Laid-Open No. 2001-195516 Summary of the Invention [Problem to be solved by the invention]

[0004] In light of the above-described techniques, the present disclosure aims to provide a processing device, a processing program, and a processing method that can process document information more efficiently through various embodiments. [Means for solving the problem]

[0005] According to one aspect of the present disclosure, there is provided a processing device having at least one processor, wherein the at least one processor is configured to acquire input document information, determine whether the acquired document information includes contract information, and execute processing to classify the acquired document information according to the result of the determination.

[0006] According to one aspect of the present disclosure, there is provided a processing program that, when executed by at least one processor, acquires input document information, determines whether the acquired document information includes contract information, and causes the at least one processor to function to classify the acquired document information according to the results of the determination.

[0007] According to one aspect of the present disclosure, there is provided a "processing method executed by at least one processor, the processing method including the steps of acquiring input document information, determining whether the acquired document information includes contract information, and classifying the acquired document information according to the result of the determination." [Effects of the Invention]

[0008] According to the present disclosure, it is possible to provide a processing device, a processing program, and a processing method that can process document information more efficiently.

[0009] It should be noted that the above effects are merely illustrative for the sake of convenience and are not limiting. In addition to or instead of the above effects, any effect described in this disclosure or an effect obvious to a person skilled in the art may be achieved. [Brief explanation of the drawings]

[0010] [Figure 1] FIG. 1 is a block diagram showing the configuration of a processing system 1 according to an embodiment of the present disclosure. [Figure 2]FIG. 2 is a block diagram showing a configuration of the server device 100 according to an embodiment of the present disclosure. [Figure 3A] FIG. 3A is a diagram conceptually illustrating a document management table stored in the server device 100 according to an embodiment of the present disclosure. [Figure 3B] FIG. 3B is a diagram conceptually illustrating an example of document information stored in the server device 100 according to an embodiment of the present disclosure. [Figure 4] FIG. 4 is a diagram showing a processing flow executed in the server device 100 according to an embodiment of the present disclosure. [Figure 5] FIG. 5 is a diagram showing a processing flow executed in the server device 100 according to an embodiment of the present disclosure. [Figure 6] FIG. 6 is a diagram showing a processing flow executed in the server device 100 according to an embodiment of the present disclosure. [Figure 7] FIG. 7 is a diagram showing a processing flow executed in the server device 100 according to an embodiment of the present disclosure. [Figure 8A] FIG. 8A is a diagram showing an example of a screen output on the terminal device 200 according to an embodiment of the present disclosure. [Figure 8B] FIG. 8B is a diagram showing an example of a screen output on the terminal device 200 according to an embodiment of the present disclosure. [Figure 8C] FIG. 8C is a diagram showing an example of a screen output on the terminal device 200 according to an embodiment of the present disclosure. [Figure 8D] FIG. 8D is a diagram showing an example of a screen output on the terminal device 200 according to an embodiment of the present disclosure. DETAILED DESCRIPTION OF THE INVENTION

[0011] 1. Overview of Processing System 1 The processing system 1 according to the present disclosure is a system used to determine whether acquired document information includes contract information and classify the acquired document information according to the results of the determination. In particular, the processing system 1 acquires document information input via an input interface of a user's terminal device and determines whether the acquired document information includes contract information. The processing system 1 then classifies the document information according to the results of the determination. If the acquired document information includes contract information as described above, the processing system 1 can perform appropriate processing according to the classification results, such as performing an analysis process of the contract information.

[0012] In this disclosure, document information refers to information stored with the intention of being referenced by individuals or organizations. Examples of such document information include various types of documents, such as official documents, contracts, minutes, rules, notices, regulations, invoices, estimates, reports, notifications, guides, and regulations. Document information may be written in any language, such as Japanese, English, Chinese, or a combination of these. Such document information may be in any format, such as document data, presentation data, image data, print layout data, or text data extracted from files in these formats.

[0013] Contract information is one type of document information and contains legally binding content. For example, it is used to prove at least one expression of intent or the fact of an agreement between two or more parties (which may be individuals or organizations), particularly the formation of a contract. Examples of such contract information include non-disclosure agreements, outsourcing agreements, master transaction agreements, development outsourcing agreements, license agreements, donation agreements, purchase and sale agreements, lease agreements, settlement agreements, and joint research agreements, as well as various other documents that can prove the facts or formation of the above contracts, such as memoranda, regulations, rules, agreements, applications, orders, requests, memoranda, and receipts. As described above for document information, such contract information can be written in any language, including Japanese, English, Chinese, or a combination of these. Such contract information can be in any format, such as document data, presentation data, image data, print layout data, or text data extracted from files in these formats. In the following description, an outsourcing contract will be used as an example of contract information, but the present invention is not limited to this.

[0014] 2. Configuration of Processing System 1 Fig. 1 is a block diagram showing a configuration of a processing system 1 according to an embodiment of the present disclosure. According to Fig. 1, the processing system 1 includes at least a server device 100 and a terminal device 200, which are communicatively connected via a wired or wireless network. The server device 100 determines whether document information acquired from the terminal device 200 includes contract information, and classifies the acquired document information according to the result of the determination. The terminal device 200 receives a user's operation input via an input interface to input document information, and displays various information received from the server device 100 (e.g., a document determination screen).

[0015] In the present disclosure, the processing device refers to the server device 100, the terminal device 200, or a combination thereof. In other words, although the following describes a case where the server device 100 functions as a processing device, the terminal device 200 can also function as a processing device. In addition, in the present disclosure, the storage and processing performed by the processing device may be distributed to other terminal devices, other server devices, etc. In other words, the processing device is not limited to those configured in a single housing, but includes the server device 100, the terminal device 200, other server devices, other terminal devices, or a combination thereof.

[0016] 1, only one terminal device 200 is shown. However, multiple users can use the processing system 1. That is, the number of terminal devices 200 is not necessarily limited to one, but multiple terminal devices 200 may be included depending on the number of users.

[0017] 3. Configuration of Server Device 100 FIG. 2 is a block diagram showing the configuration of a server device 100 according to an embodiment of the present disclosure. According to FIG. 2, the server device 100 includes a processor 111, a memory 112, and a communication interface 113. These components are electrically connected to one another via control lines and data lines. The server device 100 does not need to include all of the components shown in FIG. 2; some components may be omitted, or other components may be added. For example, an external memory, a database device, a server device, or the like connected in a communicable manner as memory may be used. Furthermore, some processing may be distributed and executed among processing devices, including other server devices. In other words, the server device 100 is not limited to a single device, but may be distributed across multiple devices depending on the information handling and processing load.

[0018] The processor 111 functions as a control unit that controls the other components of the processing system 1 based on a processing program stored in the memory 112. Based on the processing program stored in the memory 112, the processor 111 determines whether or not acquired document information includes contract information, and executes processing to classify the document information based on the result of the determination. Specifically, based on the processing program stored in the memory 112, it executes "processing to acquire input document information" and "processing to classify acquired document information based on the result of the determination." The processor 111 is mainly composed of one or more CPUs, but may also be appropriately combined with a GPU, FPGA, etc.

[0019] The memory 112 is composed of RAM, ROM, non-volatile memory, HDD, SSD, etc., and functions as a storage unit. The memory 112 stores instructions and commands for various controls of the processing system 1 according to this embodiment as processing programs. Specifically, the memory 112 stores programs to be executed by the processor 111, such as "processing for acquiring document information input via an input interface" and "processing for classifying the acquired document information according to the determination result." In addition to these programs, the memory 112 also stores various information stored in a document management table, etc. Note that this information does not need to be constantly stored in the memory 112 within the server device 100, but may be stored in a database device installed remotely. In this case, the database device is also included in the memory 112.

[0020] The communication interface 113 functions as a notification unit for transmitting and receiving various information to and from the terminal device 200 connected via a wired or wireless network. Examples of the communication interface 113 include a wired communication connector such as a USB or SCSI, a wireless communication transmitting / receiving device for broadband wireless communication such as wireless LAN, Bluetooth (registered trademark), or LTE, or an infrared wireless communication, and various connection terminals for printed circuit boards or flexible circuit boards. The communication interface 113 receives document information from the terminal device 200 and transmits output information of a document judgment screen to the terminal device 200, for example.

[0021] 4. Other equipment The configuration of the terminal device 200 includes, for example, a processor functioning as a control unit, a memory functioning as a storage unit, an input interface functioning as an input unit, an output interface functioning as an output unit, and a communication interface functioning as a communication unit. These components are electrically connected to each other via control lines and data lines. Note that the terminal device 200 does not necessarily need to include all of these components; it may be configured with some of these components omitted, or other components may be added. The terminal device 200 may be any device capable of communicating with the server device 100 via a wired or wireless network. Examples of the terminal device 200 include smartphones, tablet devices, laptop PCs, desktop PCs, scanners, photographing devices, and multifunction peripherals. Note that, as described above, when there are multiple users, multiple terminal devices 200 are used for each user, but the terminal devices 200 may each be a different type of terminal device. Furthermore, it is not necessary for one terminal device 200 to exist for one user; multiple users may use one terminal device 200, or one user may use multiple terminal devices 200.

[0022] The terminal device 200, for example, inputs document information related to various documents such as contracts via an input interface by having a processor process a program stored in memory, and transmits the input document information to the server device 100 via a communication interface. Specifically, the processor of the terminal device 200 photographs a document via a camera unit functioning as an input interface and inputs the photographed image data as document information. The processor of the terminal device 200 also receives user input via an operation unit such as a touch panel functioning as an input interface and inputs a file in a selected document format as document information. The processor of the terminal device 200 also captures document image data via a scanner unit via an operation unit such as a touch panel functioning as an input interface, and inputs the captured image data as document information. The processor of the terminal device 200 transmits the document information input in this manner to the server device via the communication interface.

[0023] The terminal device 200, for example, causes a processor to process a program stored in memory, and further outputs various pieces of output information received via a communication interface via the output interface. Specifically, the processor of the terminal device 200 receives output information of a document judgment screen relating to document information from the server device 100 via the communication interface, and outputs the screen to an output interface such as a display.

[0024] In this embodiment, when the server device 100 acquires document information, it inputs the document information into a trained judgment model to determine whether the document information contains contract information. Therefore, the processing system 1 may further include a model generation device in some cases. The model generation device includes a processor, a memory, and a communication interface, with these elements electrically connected to each other via control lines or data lines. The model generation device generates a trained judgment model by having the processor process a program stored in the memory, learning a pair of training document information prepared for training and training judgment result information that labels the document information.

[0025] Note that such a model generation device is not necessarily required, and the server device 100 or the terminal device 200 may generate a trained determination model.

[0026] 5. Various information used in processing in the processing system 1 3A is a diagram conceptually illustrating a document information table stored in the server device 100 according to an embodiment of the present disclosure. According to FIG. 3A, the document management table of this embodiment stores document information, classification information, template information, attribute information, related contract information, risk information, and the like, in association with document ID information.

[0027] The "document ID information" is, for example, information unique to each piece of document information and is information for identifying each piece of document information. The document ID information is generated by the server device 100, for example, every time new document information is received.

[0028] "Document information" is information stored with the assumption that it will be referenced by individuals or organizations. "Classification information" is information assigned based on the result of determining whether the document information contains contract information. In other words, the classification information can be in any form, such as "contains contract information" or "does not contain contract information," as long as it can identify whether the document information contains contract information. Furthermore, if contract information is included, classification information may be stored based on the type of contract, such as a service contract or a non-disclosure agreement. Similarly, if contract information is not included, classification information may be stored based on the type of non-contract document, such as an employee invention policy or work rules. "Template information" is stored when the document information includes contract information and is information for identifying which party provided the contract stored as the contract information. That is, the template information may be in any form, such as information indicating the position of "our company," "our organization," "yourself," "another company," "another organization," or "the other party," or information indicating that it is one of the templates stored in the system (for example, the name of the template or an ID that can identify the template). Furthermore, the template information may not only indicate which party actually provided the contract template, but also the results of the template determination process. In the latter case, this may differ from the fact of who actually provided it.

[0029] "Attribute information" is information that is stored when document information includes contract information, and indicates the attributes of the document information. Such attribute information includes, for example, information that indicates the characteristics of the contract and information separately entered by the user. Examples of attribute information include the title of the contract, the names of the parties to the contract, the transaction amount, the contract start date, the contract end date, whether or not automatic renewal occurs, the contract period, the contract termination notice deadline, and the contract conclusion date. Note that attribute information only needs to be stored when at least contract information is included, and naturally attribute information may also be stored even if contract information is not included.

[0030] "Related contract information" is information stored when document information includes contract information, and is information indicating other contracts related to the contract indicated by the contract information. For example, if the contract indicated by the contract information is a service outsourcing contract, a memorandum concluded to change the content of that service outsourcing contract corresponds to the related contract. When there is a related contract as described above, the related contract information stores information that can identify the relationship, such as document ID information assigned to the related contract. Note that related contract information only needs to be stored when at least contract information is included, and naturally related contract information may be stored even if contract information is not included. Furthermore, when there is no related contract, related contract information is not stored, or information indicating that there is no related contract is stored.

[0031] "Risk information" is information stored when document information includes contract information. It indicates the results of a risk assessment of the contract indicated by the contract information. Such risk information includes information indicating a comprehensive assessment based on the entire contract, information indicating the results of risk assessment of individual clauses included in the contract on an article-by-article or paragraph-by-paragraph basis, and information indicating the results of risk assessment of the words, phrases, or sentences that make up individual clauses. Examples of risk information include classification expressions such as "high," "medium," or "low" that indicate the level of risk, numerical values, sentence expressions that indicate the level of risk, risk content, risk countermeasures, and combinations thereof. Risk information is sufficient to be stored when at least contract information is included; it may also be stored even if contract information is not included. Furthermore, if no risk information exists, either no risk information is stored or information indicating the absence of risk information is stored.

[0032] In addition, in such a document management table, other information may be stored as appropriate, such as user ID information indicating the user who entered each document information, authority information indicating the authority of the user, and organization ID information identifying the organization to which the user belongs.

[0033] FIG. 3B is a diagram conceptually illustrating an example of document information stored in the server device 100 according to an embodiment of the present disclosure. FIG. 3B illustrates document information B1 including contract information as an example of document information. Document information B1 is composed of a plurality of pieces of part information as shown as part information S1 to S20. Part information is document information divided into predetermined units. In the example of FIG. 3B, an example is given in which page units are used as units for dividing document information, but naturally, this is not limited to page units, and any unit such as unit, item, page, sentence, phrase, or word can be used.

[0034] 3B includes parts information S1 to S4, which is the main text of the service contract, parts information S5 to S7, which is an official document (e.g., a registry) of a company (Corporation Y) that is a party (opponent) to the service contract, parts information S8 to S17, which is a non-disclosure agreement concluded with the parties to the service contract, and parts information S18 to S20, which is the minutes of negotiations between the parties to the contract. That is, document information B1 includes parts information S1 to S4, parts information S5 to S7, parts information S8 to S17, and parts information S18 to S20, which are taken in, for example, in image data format and configured as an integrated data file.

[0035] In this embodiment, it is determined whether or not document information B1 contains contract information, but it is also possible to make this determination in units of part information that makes up document information B1. In the example of Figure 3B, part information S1 to S4 and part information S8 to S17, which are contract information, are included. Therefore, document information B1 as a whole may be determined to contain contract information. Alternatively, part information S1 to S4 and part information S8 to S17, which are contract information, may be extracted from document information B1, and part information S1 to S4 may be stored as new document information B1-1 and part information S8 to S17 may be further stored as new document information B1-2 in the document management table.

[0036] The determination may be output on a page-by-page basis, or may be output as information indicating a range of the same document information. Specifically, the determination may be output that S1, S2, S3, and S4 of the part information of document information B1 contain contract information, or that the range of part information S1 to S4 contains contract information.

[0037] 6. Processing flow executed by the server device 100 Fig. 4 is a diagram showing a processing flow executed in the server device 100 according to an embodiment of the present disclosure. Specifically, Fig. 4 is a diagram showing a series of processing flows from receiving document information from the terminal device 200, determining whether the document information includes contract information, and outputting the results as a document determination screen. The processing flow is mainly performed by the processor 111 of the server device 100 reading and executing a program stored in the memory 112.

[0038] 4, in this embodiment, the processor 111 acquires document information from, for example, the terminal device 200 via the communication interface 113 (S111). In this case, the terminal device 200 receives input of document information via the input interface through processing by the processor of the terminal device, and transmits the document information input via the communication interface to the server device 100. Such input of document information is, for example, - Photographing a document via a camera unit that functions as an input interface, and inputting the photographed image data as document information Accepting user input via an operation unit such as a touch panel that functions as an input interface, and inputting a file in the selected document format as document information. - Through an operation unit such as a touch panel that functions as an input interface, image data of a document is captured via a scanner unit, and the captured image data is input as document information. This can be done by a variety of methods and procedures, such as:

[0039] The method for obtaining document information is not limited to the above method. For example, document information can be obtained by the following method: A plurality of pieces of document information stored in the terminal device 200 are transferred to a server device of the system using a batch upload system or a batch transfer system, and are acquired by the server device 100 receiving the information from the server device. The server device 100 receives and acquires document information specified by the user from a server device that provides a cloud storage service or an electronic contract service used by the user of the terminal device 200. When document information is uploaded from the terminal device 200 to a server device that provides a cloud storage service or an electronic contract service used by the user of the terminal device 200, the document information is automatically transferred to the server device 100 and acquired. This can be done by a variety of methods and means.

[0040] Furthermore, the server device 100 may not be provided exclusively for performing the various processes (for example, content analysis process, etc.) described in Fig. 4, but may be provided as part of a server device that provides a cloud storage service, an electronic contract service, etc. In such a case, for example, document information is obtained by In order to use a cloud storage service or an electronic contract service used by the user of the terminal device 200, document information is acquired by uploading it from the terminal device 200 to a server device that provides the service. This can be done by a variety of methods and means.

[0041] In this way, the acquisition of document information is not limited to directly receiving document information input into terminal device 200, but may also be acquired from other server devices, etc., and the method and means, the entity that inputs the document information, and the source of the document information may be any.

[0042] When the processor 111 receives document information, it generates new document ID information and stores the received document information in the document management table in association with the generated document ID information. Note that the document information may be stored, for example, in association with the case information to which the document information relates. Case information is information indicating a case, such as case ID information. A case is, for example, a unit of work, such as review of a contract related to certain document information. The case or case information may be set before the input of the document information, or may be generated or set as a trigger when the document information is input.

[0043] The processor 111 reads the stored document information from the document management table and inputs it to the trained judgment model to determine whether the document information contains contract information (S112). As a result, the processor 111 obtains as an output from the trained judgment model the judgment result as to whether the input document information contains contract information.

[0044] Here, Fig. 5 is a diagram showing a processing flow executed in the server device 100 according to an embodiment of the present disclosure. Specifically, Fig. 5 is a diagram showing an example of a processing flow for generating a trained judgment model used in S112 of Fig. 4. This processing flow is mainly performed by the processor 111 of the server device 100 reading and executing a program stored in the memory 112. The processing for generating the trained judgment model shown in Fig. 5 is performed before the determination of whether or not the contract information shown in Fig. 4 is included.

[0045] 5, the processor 111 executes a step of acquiring learning document information (learning document information) (S211). An example of the learning document information is the document information illustrated in FIG. 3B, but it may also be document information that does not include any contract information at all, or document information that contains only contract information. The processor 111 then executes a processing step of assigning a correct label indicating that the part information constituting each piece of document information is contract information, based on a determination by, for example, an administrator of the processing system 1 (S212). After the labeling is completed, the processor 111 executes a step of storing the assigned correct label information as determination result information in association with the learning document information (S213).

[0046] Once the training document information and the associated correct label information are obtained, the processor 111 executes a step of using them to perform machine learning of a determination pattern for determining whether each piece of part information constituting the document information is a contract document (S214). As an example, the machine learning is performed by providing a set of information to a neural network that combines neurons, and repeatedly learning while adjusting the parameters of each neuron so that the output from the neural network is the same as the correct label information. Then, a step of acquiring a trained determination model is executed (S215). The acquired trained determination model may be stored in the memory 112 of the server device 100 or in another device connected to the server device 100 via a wired or wireless network.

[0047] In the above, a neural network is used as a learning machine, but it is also possible to use learning machines that use other neural networks, such as convolutional neural networks, multi-layer Herceptrons (MLP), long short-term memory (LSTM), gated recurrent units (GRUs), graph neural networks (GNNs), and transformers; gradient boosting decision trees (GBDTs) such as LightGBM (Light Gradient Boosting Machine), XGBoost, and CatBoost; ridge regression, logistic regression, support vector regression (SVR), nearest neighbor methods, decision trees, regression trees, and random forests.

[0048] Furthermore, while FIG. 5 illustrates a trained judgment model generated by training a pair of training document information and a correct label, it is also possible to use a trained judgment model that utilizes deep learning, such as a generative trained judgment model. Among such generative trained judgment models, a trained judgment model called a large language model (LLM) is particularly preferred. More preferred examples of such trained judgment models include Bidirectional Encoder Representations from Transformers (BERT) and Generative Pre-trained Transformer (GPT), and among these, ChatGPT or GPT-4 are particularly preferred. In this way, a general-purpose trained model can be used as the trained judgment model, rather than one generated solely for the judgment process.

[0049] The trained judgment model exemplified above may be stored as a program in memory 112 in server device 100 and processed by processor 111 executing the program, or may be stored as a program in memory in another processing device communicatively connected to server device 100 and processed by a processor in that processing device. In the latter case, processor 111 of server device 100 transmits input information in the form of a question to the processing device and obtains answer information as output from that processing device.

[0050] Furthermore, the trained judgment model does not need to be formed by a single trained judgment model, and multiple trained judgment models can be combined and used. As an example, trained judgment models with the same training document information but different learning device structures can be used, or one trained judgment model can use a large-scale language model trained based on general-purpose training information, while the other trained judgment model can use a trained judgment model trained based on training document information including contract information, etc. When multiple trained judgment models are used in this way, output can be obtained by ensembling the answer information from each trained judgment model. Furthermore, the training document information input to the trained judgment model and the document information used in the judgment process may be converted into a numerical representation (e.g., vector value) that is easy to process by the trained judgment model by performing a conversion process such as embedding as appropriate.

[0051] Furthermore, in FIG. 5, the case where each process is performed by the processor 111 of the server device 100 has been described, but the process may also be generated by, for example, a model generation device connected to the server device 100 via a wired or wireless network.

[0052] 4, when processor 111 obtains as output from the trained judgment model the judgment result as to whether or not contract information is included in the input document information, processor 111 determines whether or not the judgment result indicates that contract information is included (S113). If the judgment result indicates that contract information is included, processor 111 assigns classification information called "contract document" indicating that contract information is included, and stores the classification information in the document management table in association with the document ID information (S114). On the other hand, if the judgment result indicates that contract information is not included, processor 111 assigns classification information called "non-contract document" indicating that contract information is not included, and stores the classification information in the document management table in association with the document ID (S119).

[0053] 3B, the document information may include parts information S1 to S4 and S8 to S17, which are contract information, and parts information S5 to S7 and S18 to S20, which are non-contract information. In such cases, it is preferable that processor 111 extracts each of the parts information S1 to S4 and S8 to S17, which are determined to be contract information. Specifically, processor 111 divides the data files constituting document information B1 into data files constituting parts information S1 to S4, data files constituting parts information S5 to S7, data files constituting parts information S8 to S17, and parts information S18 to S20. Processor 111 then generates new document ID information B1-1 for parts information S1 to S4, and stores the document information (parts information S1 to S4) and classification information indicating a "contract document" in association with the document ID information. Similarly, processor 111 generates new document ID information B1-2 for parts information S8 to S17, and stores the document information (parts information S8 to S17) and classification information indicating "contract document" in association with the document ID information. Similarly, processor 111 generates new document ID information B1-3 for parts information S5 to S7, and stores the document information (parts information S5 to S7) and classification information indicating "non-contract document" in association with the document ID information. Similarly, processor 111 generates new document ID information B1-4 for parts information S18 to S20, and stores the document information (parts information S18 to S20) and classification information indicating "non-contract document" in association with the document ID information. Then, in subsequent processing, each newly extracted document information is processed. This allows documents such as contracts to be handled more appropriately.

[0054] Note that this type of processing is an example of a case where contract information and non-contract information are mixed in the document information. In other words, when they are mixed, the processor 111 may determine that the document information as a whole contains contract information and assign "contract document" to indicate that it contains contract information. In this case, the entire document information may be processed as a single unit in subsequent processing as well.

[0055] 4, only two classifications, contractual documents and non-contractual documents, are assigned as classification information, but more detailed classifications can be assigned by, for example, further subdividing the labels when generating the trained decision model and then training the model. That is, when contract information is included, processor 111 may store, as classification information, classifications according to the types of contracts, such as outsourcing contracts, non-disclosure agreements, and purchase orders. When contract information is not included, processor 111 may store, as classification information, classifications according to the types of non-contractual documents, such as employee invention regulations and work rules.

[0056] 4, a determination is made as to whether or not contract information is included in the trained determination model, but this determination may also be made by further processing the output from the trained determination model by the processor 111. Also, the information on the output of the above-mentioned subdivided contract types and non-contract documents may be simply rounded down to contract information or non-contract documents.

[0057] Next, if the processor 111 determines in S113 and S114 that the document information contains contract information and is assigned the classification of "contract document," it executes a template determination process to determine which party provided the document information (S115). As an example of the template determination process, the processor 111 stores contract information (template information) of a template contract prepared by a user of a service provided by the processing system 1 or an organization to which the user belongs in advance. The processor 111 then determines whether the template was prepared by itself by calculating a similarity (e.g., cosine similarity, Jaccard coefficient, etc.) with the template information. If the processor 111 determines that the document information is its own template based on the determination based on the similarity with the template (S116), the processor 111 assigns a label "its own template" to the document information and stores the assigned label in association with the document ID information of the document information as template information (S117).

[0058] Next, if it is determined in S113 and S114 that the document information contains contract information and is classified as a "contract document," the processor 111 executes a content analysis process on the document information (S118). The content analysis process may be any process that analyzes the content of the contract indicated by the contract information. For example, - Processing to extract attribute information from contract information - Processing to identify related contract information from contract information - Processing to analyze risks in contracts based on contract information A combination of these processes Examples include:

[0059] Here, Fig. 6 is a diagram showing a processing flow executed in the server device 100 according to an embodiment of the present disclosure. Specifically, Fig. 6 is a diagram showing an example of the processing flow of "processing to extract attribute information from contract information" and "processing to identify related contract information from contract information" from the content analysis processing executed in S118 of Fig. 4. This processing flow is mainly performed by the processor 111 of the server device 100 reading and executing a program stored in the memory 112.

[0060] 6, the processor 111 reads out a file constituting document information including contract information (S311) and extracts attribute information contained in the document information (S312). The extraction process is performed by the processor 111 by executing a document analysis program on the file constituting the document information. As an example, the processor 111 first extracts text information by analyzing the file constituting the document information. Note that this text information may be text information extracted and stored during the document type determination process. The processor 111 then performs linguistic analysis on the extracted text information to extract information on multiple pre-set items, such as the contract title, names of the parties to the contract, transaction amount, contract start date, contract end date, whether or not the contract is automatically renewed, contract period, contract termination notice deadline, and contract conclusion date.

[0061] When the information for each item is extracted, the processor 111 stores the extracted information in the attribute information in association with the document ID information (S313). Note that for items that could not be extracted, null data is stored.

[0062] Next, the processor 111 generates a search term based on the extracted attribute information (S314). The search term is information used to search for candidates for other contracts (related contracts) related to the contract indicated by the contract information read out in S311, and corresponds to a so-called search query. The processor 111 sets, for example, the names of the parties to the contract, the title of the contract, the contract conclusion date, etc., from the attribute information extracted in S312, as the search term.

[0063] Next, the processor 111 searches all document information stored in the document management table using the search phrase generated in S314 (S315). Specifically, the processor 111 calculates the degree of relevance of each piece of document information with the search phrase, and identifies document information whose calculated degree of relevance is equal to or greater than a predetermined value. The processor 111 then extracts, from the identified document information, the document ID information of document information whose classification information is stored as "contract document" as a candidate for related contracts. The processor 111 transmits each document ID information and each document information as a candidate for related contracts to the terminal device 200 via the communication interface 113 (S316).

[0064] On the terminal device 200 that has received the candidate related contract information, a list of candidate related contracts is displayed via the output interface through processing by the processor. The processor of the terminal device 200 then accepts user input via the input interface, selects a related contract, and transmits the selection result to the server device via the communication interface. When the processor 111 of the server device 100 receives the selection result via the communication interface 113 (S317), it stores the received selection result as related contract information in association with the document ID information (S318).

[0065] This completes the processing flow for performing the "processing to extract attribute information from contract information" and the "processing to identify related contract information from contract information" out of the content analysis processing executed in S118 of Fig. 4. Note that in Fig. 6, both the "processing to extract attribute information from contract information" and the "processing to identify related contract information from contract information" are executed, but it goes without saying that only one of these processes may be executed, or other content analysis processes may be additionally executed.

[0066] 7 is a diagram showing a processing flow executed in the server device 100 according to an embodiment of the present disclosure. Specifically, Fig. 7 is a diagram showing an example of the processing flow of "processing for analyzing risks in a contract from contract information" in the content analysis processing executed in S118 of Fig. 4. This processing flow is mainly performed by the processor 111 of the server device 100 reading and executing a program stored in the memory 112.

[0067] 7, the processor 111 reads a file constituting document information including contract information (S411) and inputs the read document information into the trained risk analysis model (S412). Specifically, the processor 111 breaks down the text information extracted from the target document information into individual clauses constituting the contract through language analysis. Then, the processor 111 inputs the text information constituting each clause into the trained risk analysis model for each of the broken down clauses. The processor 111 obtains the risk analysis results for each clause as output from the trained risk analysis model.

[0068] A trained risk analysis model can be generated, for example, as follows. First, a processor generates training text information by extracting text information for each individual clause that constitutes a training contract. The processor also generates label information by labeling the generated training contract document information with information indicating the degree of risk (e.g., "high," "medium," and "low") in advance. The processor then provides a neural network that combines neurons with the training text information and the label information, and repeats learning while adjusting each parameter so that the output from the neural network is the same as the label information. In this way, a trained risk analysis model is obtained.

[0069] Note that, as with the trained judgment model shown in Figure 5, such a trained risk analysis model can use a learner other than a neural network, or can utilize a generative trained analysis model such as a large-scale language model. Also, as with the trained judgment model shown in Figure 5, the trained risk analysis model can combine multiple trained risk analysis models.

[0070] Furthermore, the trained risk analysis model may be generated or trained not only by the server device 100 but also by a model generation device connected to the server device 100 via a wired or wireless network.

[0071] In addition, the learned risk analysis model may be stored as a program in the memory 112 of the server device 100 and processed by the processor 111 executing the program, or it may be stored as a program in the memory of another processing device that is communicatively connected to the server device 100 and processed by the processor in that processing device.

[0072] Server device 100 stores various risk-related information, such as risk content and how to deal with the risk, in association with text information that is the level of risk, the title of the clause, and the content of the clause. Therefore, when processor 111 acquires an analysis result indicating the level of risk from the trained risk analysis model, it acquires the risk content and how to deal with the risk based on the analysis result and the title and text information of each clause input to the trained analysis model. Then, processor 111 stores the analysis result, the risk content, the how to deal with the risk, etc. as risk information (S413).

[0073] This completes the processing flow for performing "processing for analyzing risks in a contract from contract information" in the content analysis processing executed in S118 of Fig. 4. Note that Fig. 7 describes the case where only "processing for analyzing risks in a contract from contract information" is executed, but each processing shown in Fig. 6 may also be executed additionally.

[0074] 4, when the various content analysis processes are completed, the processor 111 generates output information for a document judgment screen based on the attribute information, related contract information, risk information, etc. obtained by the content analysis processes. Then, the processor 111 transmits the generated output information for the document judgment screen to the terminal device 200 via the communication interface 113 (S120).

[0075] 4, if the input document information does not include contract information, "non-contract document" is stored as the classification information, and the execution of the template determination process and content analysis process performed on document information classified as "contract document" is restricted. Specifically, the processor 111 skips the execution of the template determination process and content analysis process on document information classified as "non-contract document," omits part of the process, or executes a process different from the process content. This ends the processing flow.

[0076] As such, the template determination process and the content analysis process shown in Figures 6 and 7 generally impose a heavy processing burden on the server device 100. Executing such processes for all document information would result in unnecessary processing burden, so the template determination process and content analysis process are executed only for document information that includes contract information, as shown in Figure 4. This reduces the processing burden on the server device and enables the process to be executed more efficiently for the document information received in S111 of Figure 4.

[0077] 7. Example of document judgment screen 8A to 8D are diagrams showing examples of screens output on the terminal device 200 according to an embodiment of the present disclosure. Specifically, Fig. 8A to 8D are diagrams showing examples of document determination screens output on the terminal device 200 in S120 of Fig. 4. That is, Fig. 8A to 8D show examples of document determination screens output via an output interface on the terminal device 200 that has received output information for the document determination screen from the server device 100.

[0078] FIG. 8A shows a document determination screen 10 of the document determination screen, which displays attribute information extracted in the content analysis process of FIG. 6 after being classified as a contract document in S113 of FIG. 4 or the like. The document determination screen 10 includes at least a classification information display area 11, a document information display area 12, a related information display area 13, and a template area 14. The classification information display area 11 is an area that displays classification information resulting from a classification based on the determination result of whether or not the document contains contract information in S113 of FIG. 4 or the like. In the example of FIG. 8A, "contract" is displayed in the classification information display area 11, which indicates that the document information displayed in the document information display area 12 contains contract information. When a user inputs an operation on a downward-pointing triangle icon on the right side of the classification information display area 11 via an input interface, it is possible to switch to other document information to which other classification information has been assigned.

[0079] The document information display area 12 is an area for displaying the document information 15 received in S111 of FIG. 4 in any format, including document data, presentation data, image data, print layout data, and text data extracted from files in these formats. The example in FIG. 8A shows an example of display in image data format, but the document information may be displayed in another data format, depending on the user's preference. Referring to FIG. 8A, the document information 15 displayed in the document information display area 12 includes the title of the contract, "Service Outsourcing Contract," as well as text such as "X Corporation enters into..." and "Article 1 (Purpose)...." In other words, by displaying the specific content of the document information 15 in the document information display area 12, it is possible to confirm the document information 15 by comparing it with information indicating the results of subsequent processing.

[0080] The related information display area 13 is an area for displaying at least one of various pieces of information (e.g., attribute information, related contract information, or risk information shown in FIG. 3A ) acquired by various processes performed on document information. The related information display area 13 includes an attribute icon 16 and a related contract icon 17 at its upper portion. That is, when a user's operation input for either the attribute icon 16 or the related contract icon 17 is accepted via the input interface, information corresponding to the icon for which the operation input was made is displayed in the related information display area 13. In FIG. 8A , the attribute icon 16 is displayed so as to be distinguishable from the related contract icon 17, indicating that an operation input for the attribute icon 16 has been accepted. Therefore, the related information display area 13 displays the attribute information extracted and stored by the processes of S312 and S313 in FIG. 6 . Specifically, the related information display area 13 displays the following attribute information: the contract title, the names of the parties, the transaction amount, whether the contract can be changed, the contract start date, the contract end date, whether automatic renewal is enabled, the contract period, and the contract termination notice deadline. The related information display area 13 also includes a confirmed icon 18 and a correction icon 19. When a user inputs an operation for each of these icons, it is possible to store a flag indicating "confirmed" for the stored attribute information or to execute a correction process to correct the content.

[0081] The template area 14 is an area for displaying template information acquired in steps S115 to S117 of Fig. 4 to identify which party provided the template for the contract. In the example of Fig. 8A, a check mark is entered in the checkbox next to the display "Company template" in the template area 14. This indicates that information indicating that the template information for the document information 15 displayed in the document information display area 12 is a template prepared by the user is stored. In other words, the user can confirm that the document information 15 was created based on the user's own template.

[0082] Next, Fig. 8B shows a document determination screen 10 for displaying related contract information that has been classified as a contract document in S113 of Fig. 4 and that has been identified in the content analysis process of Fig. 6. Of the document determination screen 10 shown in Fig. 8B, the classification information display area 11, document information display area 12, and template area 14 are the same as those in Fig. 8A, and therefore their description will be omitted.

[0083] 8B, the related contract icon 17 in the related information display area 13 is displayed so as to be distinguishable from the attribute icon 16, indicating that an operation input for the related contract icon 17 has been accepted. Therefore, the related information display area 13 displays the related contract information identified by the processes of S314 to S318 in FIG. 6. Specifically, the related information display area 13 displays the attribute information for the memorandum of change to the outsourcing terms and the non-disclosure agreement as the related contract information. The related information display area 13 also includes an add icon 22 and a modify icon 23. When a user's operation input for each of these icons is accepted, it is possible to add to or modify the information stored as the related contract information as desired by the user.

[0084] Next, Fig. 8C shows a document determination screen 30 of the document determination screen when a document is classified as a contract document in S113 of Fig. 4 or the like and displays risk information analyzed in the content analysis process of Fig. 7. Note that, among the document determination screens shown in Fig. 8C, the classification information display area 31, document information display area 32, and template area 34 are similar to the classification information display area 11, document information display area 12, and template area 14 of Fig. 8A, and therefore description thereof will be omitted.

[0085] In FIG. 8C , the related information display area 33 includes risk information. Specifically, the related information display area 33 includes an overall result area 36 that shows the results of an analysis of the risk of the entire contract indicated in the document information 35, and clause risk display areas 37 and 38 that show the results of an analysis of the risk of each clause. The clause risk display area 37 shows clauses that have been determined to have a "high" risk level as a result of analyzing the risk of each clause included in the document information 35. The clause risk display area 38 shows clauses that have been determined to have a "low" risk level as a result of analyzing the risk of each clause included in the document information 35. In other words, the clause risk display area 37 and the clause risk display area 38 have outer frames with different display styles depending on the level of risk. This allows the user to visually recognize the level of risk more intuitively.

[0086] Furthermore, each of the clause risk display areas 37 and 38 includes an indication of the degree of risk (for example, an indication such as "Importance: High" or "Importance: Low"), an indication of the content of the risk (for example, an indication such as "<Addition> Is the breakdown of the commission fee specified?" or "<Omission> Is there a provision regarding late payment penalties?"), and an indication of how to deal with the risk (for example, an indication such as "Response example: Add the following as necessary..."). In other words, each of the clause risk display areas displays the content stored as risk information in the document management table.

[0087] The overall result area 36 includes aggregated information on the results of risk analysis of each clause included in the document information 35. That is, the overall result area 36 includes the aggregated results of the number of clauses analyzed to have a "high" risk (importance) level, the number of clauses analyzed to have a "medium" risk level, and the number of clauses analyzed to have a "low" risk level.

[0088] 8A and 8B, the case where each piece of information is switched and displayed by operating the attribute icon 16 and the related contract icon 17 has been described. Similarly, for the risk information shown in Fig. 8C, a new risk icon may be provided so that each piece of information can be switched and displayed.

[0089] Next, FIG. 8D shows a document determination screen 50 of the document determination screen when the document is classified as a non-contract document in S113 or the like of FIG. 4. The document determination screen 50 includes at least a classification information display area 51, a document information display area 52, and a related information display area 53. The classification information display area 51 is an area that displays classification information that is the result of classification based on the determination result of whether or not the document contains contract information in S113 or the like of FIG. 4. In the example of FIG. 8D, "Non-contract" is displayed in the classification information display area 51, which indicates that the document information 54 displayed in the document information display area 52 is non-contract information. Note that when a user's operation input to the downward-pointing triangle icon on the right side of the classification information display area 51 is accepted via the input interface, it is possible to switch to other document information assigned with other classification information.

[0090] The document information display area 52 is an area for displaying the document information 54 received in S111 of FIG. 4 in any format, including document data, presentation data, image data, print layout data, and text data extracted from files in any of these formats. The example in FIG. 8D shows an example of display in image data format, but the document information may be displayed in another data format, depending on the user's preference. Referring to FIG. 8D, the document information 54 displayed in the document information display area 52 includes the document title "Work Rules" and text such as "Article 1 (Purpose)...." In other words, by displaying the specific content of the document information 54 in the document information display area 52, it is possible to confirm the document information 54 by comparing it with information indicating the results of subsequent processing performed on the document.

[0091] The related information display area 53 is an area for displaying various information (e.g., attribute information) obtained by various processes performed on the document information 54. The related information display area 53 displays attribute information extracted by, for example, an attribute analysis process performed on the document information 54. Specifically, the related information display area 53 displays information such as the document title and its implementation date as attribute information. The related information display area 53 also includes a confirmed icon 55 and a correction icon 56. When a user's operation input for each of these icons is accepted, it is possible to store a "confirmed" flag for the stored attribute information or to execute a correction process to correct the content.

[0092] As such, Figure 8D displays information that is different from the attribute information, related contract information, and risk information displayed for document information classified as a contract document in Figures 8A to 8C. This is because, for document information classified as a non-contract document, the execution of each process for generating the attribute information, related contract information, and risk information in Figures 6 and 7 was skipped, or at least only a part of each process was executed.

[0093] As described above, in the present embodiment, it is possible to provide a processing device, a processing program, and a processing method that can process document information more efficiently.

[0094] 8.Other 4 to 7 illustrate the use of a trained judgment model or a trained risk analysis model in the processes related to each judgment or analysis. However, using such a trained model is merely an example, and judgment or analysis may naturally be performed using a method that does not use a trained model. For example, a large number of example contract documents may be stored in advance, and the processor 111 may determine whether the input document information is a contract document or a non-contract document by calculating the similarity between the input document information and each example document or by recognizing the title of the input document information. Furthermore, if the document information is assigned classification information other than classification information indicating whether it is a contract document or a non-contract document (e.g., a classification indicating whether two or more parties are listed or a classification indicating whether an agreement or similar wording is included) or attribute information, the processor may determine whether the document information is a contract document or a non-contract document based on the other classification information or attribute information.

[0095] 6 and 7, the content analysis processes described above are "processing to extract attribute information from contract information," "processing to identify related contract information from contract information," and "processing to analyze risks in a contract from contract information." However, other content analysis processes may also be performed. Examples of such content analysis processes include a dashboard generation process that displays the results of tallying the attribute information of each document information stored in the document management table, and a document information editing process.

[0096] It is also possible to associate contract documents with non-contract documents. For example, when contract documents and non-contract documents are generated by splitting a single file, or when multiple files uploaded in a single folder contain contract documents and non-contract documents, the non-contract documents are likely to contain information that supplements the contract documents. For business efficiency, it is preferable to associate and store such multiple files. Therefore, it is preferable to associate files determined to be contract documents with documents determined to be non-contract documents, or to store them in association with a single case, or to prompt the user to associate them. This association of contract documents with non-contract documents is an example of content analysis processing.

[0097] It should be noted that the embodiments and modifications of the present disclosure are presented as examples and are not intended to limit the scope of the present disclosure. The present embodiments and modifications can be implemented in various other forms, and various omissions, substitutions, and modifications can be made without departing from the spirit of the present disclosure. These embodiments and modifications are included within the scope and spirit of the invention, and are also included in the inventions and their equivalents as set forth in the claims.

[0098] The processes and procedures described in this disclosure can be realized not only by those explicitly described in the embodiments, but also by software, hardware, or a combination thereof. Specifically, the processes and procedures described in this disclosure can be realized by implementing logic corresponding to the processes in media such as integrated circuits, volatile memory, non-volatile memory, magnetic disks, and optical storage. Furthermore, the processes and procedures described in this disclosure can be implemented as computer programs and executed by various computers, including processing devices and server devices.

[0099] Although processes and procedures described in this disclosure are described as being performed by a single device, software, component, or module, such processes or procedures may be performed by multiple devices, multiple software, multiple components, and / or multiple modules. Furthermore, although various information described in this disclosure is described as being stored in a single memory or storage unit, such information may be stored in multiple memories within a single device or multiple memories distributed across multiple devices. Furthermore, software and hardware elements described in this disclosure may be realized by integrating them into fewer components or by decomposing them into more components. [Explanation of symbols]

[0100] 1 Processing System 100 Server device 200 Terminal Device

Claims

1. A processing device comprising at least one processor, the at least one processor: Obtain the input document information, determining whether the acquired document information includes contract information; classifying the acquired document information according to the result of the determination; a processing unit configured to perform processing for:

2. The processing device according to claim 1 , wherein the determination of whether the document information includes the contract information is performed by inputting the document information into a trained determination model.

3. The processing device according to claim 2 , wherein the trained judgment model is acquired by learning based on training document information and training judgment result information indicating whether the training document information contains contract information.

4. The processing device according to claim 1 , wherein the document information includes a plurality of pieces of part information divided into predetermined units.

5. The at least one processor: determining whether or not each of the plurality of pieces of part information includes contract information; If the result of the determination is that at least one piece of part information among the plurality of pieces of part information includes contract information, it is determined that the document information includes contract information. The processing device of claim 4 configured to perform processing for:

6. The at least one processor: determining whether or not each of the plurality of pieces of part information includes contract information; If the result of the determination is that at least one piece of part information among the plurality of pieces of part information includes contract information, classification information indicating that the at least one piece of part information includes contract information is assigned to the at least one piece of part information. The processing device of claim 4 configured to perform processing for:

7. The processing device according to claim 1 , wherein, when the acquired document information includes the contract information, a content analysis process is executed to analyze the content of the contract information.

8. The processing device according to claim 7 , wherein the content analysis process is a process for acquiring attribute information of the contract information based on the content of the contract information.

9. The processing device according to claim 7 , wherein the content analysis process is a process for determining the risk of a contract indicated by the contract information based on the content of the contract information.

10. The processing device according to claim 7 , wherein execution of the content analysis process is restricted when the acquired document information does not include the contract information.

11. When executed by at least one processor, Obtain the input document information, determining whether the acquired document information includes contract information; classifying the acquired document information according to the result of the determination; A processing program that causes the at least one processor to function in such a manner.

12. A processing method executed by at least one processor, comprising: obtaining input document information; determining whether the acquired document information includes contract information; classifying the acquired document information according to the result of the determination; A processing method comprising:

Images