Program, method, information processing device, and system

Abstract

To provide a program for efficiently managing information relating to a real estate certificate by highly accurately acquiring the information from the real estate certificate.SOLUTION: A program for causing a computer including a processor and a memory to execute processing, the program causes the processor to execute: an acquisition step of acquiring registration data relating to registration of a real estate; a generation step of generating shaped data based on the registration data by using a learned model; a first storage step of extracting property data, the data relating to a property, from the shaped data and causing a storage unit to store the extracted property data; a second storage step of extracting owner data, the data relating to an owner of the property, from the shaped data and causing the storage unit to store the extracted owner data; and an association step of associating the owner data and the property data stored in the storage unit.SELECTED DRAWING: Figure 8

Description

[Technical field]

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

[0002] A system for managing information related to real estate is known (see, for example, Patent Document 1). In Patent Document 1, for example, text information with ruled line information (for example, HTML, XML file) is generated from various certificate documents, image data, etc. using OCR. Next, each item of the certificate of all details (purpose of registration, ranking number, etc.) is extracted based on the ruled line information. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] JP 2002-373197 A Summary of the Invention [Problem to be solved by the invention]

[0004] In Patent Document 1, items of documents are extracted based on text information, which is vulnerable to exception processing and requires human judgment to make corrections. Therefore, there is a high possibility of processing errors occurring and the burden on the person in charge may be increased. The purpose of this disclosure is to obtain information from real estate certified copies with high accuracy and efficiently manage information related to real estate certified copies. [Means for solving the problem]

[0005] The present disclosure provides a program for causing a computer having a processor and a memory to execute processing, the program causing the processor to execute an acquisition step of acquiring registration data related to real estate registration, a generation step of generating shaped data based on the registration data using a trained model, a first storage step of extracting property data, which is data related to a property, from the shaped data and storing the extracted property data in a memory unit, a second storage step of extracting owner data, which is data related to the owner of the property, from the shaped data and storing the extracted owner data in a memory unit, and an association step of associating the owner data stored in the memory unit with the property data. Effect of the Invention

[0006] According to the present disclosure, information can be obtained from real estate certified copies with high accuracy, and information related to real estate certified copies can be efficiently managed. [Brief description of the drawings]

[0007] [Figure 1] FIG. 2 is a block diagram showing the functional configuration of the system 1. [Diagram 2] FIG. 2 is a block diagram showing the functional configuration of the server 10. [Diagram 3] 2 is a block diagram showing the functional configuration of a user terminal 20. FIG. [Figure 4] FIG. 13 is a diagram showing the data structure of an owner database 1012. [Diagram 5] FIG. 13 is a diagram showing the data structure of a property database 1013. [Figure 6] FIG. 13 is a diagram showing the data structure of a debt database 1015. [Figure 7] FIG. 13 is a diagram showing the data structure of a creditor database 1016. [Figure 8] 1 is a flowchart showing the first half of the processing flow of the system 1. [Figure 9] 13 is a flowchart showing the second half of the processing flow of the system 1. [Figure 10] FIG. 11 is a diagram illustrating a portion of shaping data. [Figure 11] 13 is a flowchart showing the first half of the processing flow of the analysis process (S300). [Figure 12] 13 is a flowchart showing the latter half of the processing flow of the analysis process (S300). [Figure 13] 13 is a flowchart showing the latter half of the processing flow of the analysis process (S300). [Figure 14] FIG. 2 is a block diagram showing the basic hardware configuration of a computer 90. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0008] Hereinafter, an embodiment of the present disclosure will be described with reference to the drawings. In all the drawings explaining the embodiment, the same reference numerals are given to common components, and repeated explanations are omitted. Note that the following embodiment does not unduly limit the contents of the present disclosure described in the claims. In addition, not all of the components shown in the embodiment are essential components of the present disclosure. In addition, each figure is a schematic diagram and is not necessarily illustrated strictly.

[0009] <1. System 1 Configuration> The system 1 according to the present disclosure is an information processing system that manages information related to real estate registration. As shown in Fig. 1, the system 1 according to the present disclosure includes a server 10 and a user terminal 20. The server 10, the user terminal 20, and an external server S are communicatively connected via a network N. Note that, in the example shown in Fig. 1, there is one server 10 and one user terminal 20, but either or both of the server 10 and the user terminal 20 may be configured as a plurality of units.

[0010] The server 10 and the user terminal 20 are configured by a computer 90 equipped with a calculation device and a storage device. The basic hardware configuration of the computer 90 and the basic functional configuration of the computer realized by the hardware configuration will be described later. For the server 10 and the user terminal 20, descriptions that overlap with the basic hardware configuration and basic functional configuration of the computer 90 described later will be omitted.

[0011] The external server S provides access to a large-scale language model M. The large-scale language model M is an example of a trained model, and is a natural language model trained using a large number of parameters (e.g., billions to hundreds of billions) and high-level computational resources. A natural language model refers to a computer program or algorithm designed to perform natural language processing tasks. As an example, natural language processing performs processes such as morphological analysis, syntactic analysis, information extraction, and sentence generation, enabling a computer to analyze language used by humans (i.e., natural language) and perform predetermined processing.

[0012] Examples of the large-scale language model M include the GPT series (Generative Pre-trained Transformer) developed by OPEN AI and BERT (Bidirectional Encoder Representations from Transformers) developed by Google. The large-scale language model M tends to have high learning costs because it is trained using a very large amount of parameters and computational resources. In this embodiment, the learning cost is reduced by using a trained model that is publicly available from an external server S. Note that a certified copy of a real estate property registration (certificate of registered matters) is not written in text form in terms of format. Therefore, the GPT series is more preferable than BERT. In this embodiment, for example, a definition is passed to GPT, and the GPT is made to understand the context and then generate information.

[0013] <2. Server 10 Configuration> 2, the server 10 is an information processing device that manages information related to real estate registration. The server 10 includes a storage unit 101 and a control unit 104.

[0014] <2.1. Configuration of the storage unit 101 of the server 10> The memory unit 101 of the server 10 includes an application program 1011 , an owner database 1012 , a property database 1013 , a debt database 1015 , a creditor database 1016 , and a restructuring request 1014 .

[0015] The application program 1011 is a program for causing the control unit 104 of the server 10 to function as each functional unit. By executing the application program 1011, the control unit 104 provides various applications such as a web browser application.

[0016] The owner database 1012 is a database that stores information (hereinafter also referred to as owner data) about the owner of a specific real estate property (hereinafter also simply referred to as property). As shown in Fig. 4, as an example, the owner database 1012 has an item "owner ID", an item "name", an item "address", an item "owned real estate", and an item "debt information". Note that the owner database 1012 may have items other than these, or may not have any of these.

[0017] The item "owner ID" is an item for storing an identifier for uniquely identifying an owner registered in the owner database 1012. The item "owner ID" functions as a primary key of the owner database 1012. The item "owner ID" may also be referred to as a reception number.

[0018] The item "name" is an item for storing information about the owner's name.

[0019] The item "address" is an item for storing information about the owner's address.

[0020] The item "Owned Real Estate" is an item for storing information about real estate (properties) owned by an owner. The item "Owned Real Estate" stores, for example, information for identifying an owned property, such as a property ID or a property number. The item "Owned Real Estate" may also store a ranking indicating changes in ownership. The item "Owned Real Estate" may also store an owner's share of an owned property. Share is information indicating the owner's share ratio when an owned property is shared. As an example, the share holds a ratio of the share calculated as a percentage.

[0021] The item "debt information" is an item for storing identification information representing debt information. For example, a debt ID is stored in the item "debt information".

[0022] A user (a real estate agent, as an example) who uses the system 1 can add and register a new record in the owner database 1012 or update the contents of a record registered in the owner database 1012 by operating the user terminal 20. Alternatively, the server 10 executes an analysis process (S400 / FIG. 9) described below, whereby a new record is added to the owner database 1012 or the contents of an existing record are updated. The analysis process will be described in detail later.

[0023] The property database 1013 is a database that stores information about a specific property (hereinafter, also referred to as property data). As shown in Fig. 5, as an example, the property database 1013 has an item "Property ID", an item "Real Estate Number", an item "Address", an item "Land Use", an item "Registration Date", an item "Land Area", and an item "Cause". Note that the property database 1013 may have items other than these, or may not have any of these.

[0024] The item "property ID" is an item for storing an identifier for identifying a property registered in the property database 1013. The item "property ID" may also be referred to as a reception number.

[0025] The item "Real Estate Number" is an item for storing a real estate number for uniquely identifying a property. The real estate number is a 13-digit number managed by the Legal Affairs Bureau.

[0026] The item "Address" is an item for storing information about the address of the property. The item "Address" may be divided into a location and a lot number.

[0027] The item "land use" is an item for storing the main use of the land. For example, the use such as residential land is stored in the item "land use".

[0028] The item "registration date" is an item for storing the date on which the property was registered.

[0029] The item "land area" is an item for storing the area of ​​land.

[0030] The item "Cause" is used to record the cause of the registration and the date on which it occurred.

[0031] A user of the system 1 can add and register a new record in the property database 1013 or update the contents of a record registered in the property database 1013 by operating the user terminal 20. Alternatively, the server 10 executes an analysis process (S400) described below, whereby a new record is added to the property database 1013 or the contents of an existing record are updated. The analysis process will be described in detail later.

[0032] The debt database 1015 is a database that stores information about debts related to a specified property (hereinafter, also referred to as debt data). As shown in Fig. 6, as an example, the debt database 1015 has an item "debt ID", an item "borrowing date", an item "claim amount", an item "damages", an item "interest rate", an item "debtor", an item "creditor", and an item "estimated balance". Note that the debt database 1015 may have items other than these, or may not have any of these.

[0033] The "Debt ID" item is an item for storing an identifier for identifying a debt registered in the debt database 1015. The "Borrowing Date" item is an item for storing the date on which the debt was borrowed. The "Claims Amount" item is an item for storing the amount of the debt registered in the debt database 1015. The "Damage" item is an item for storing interest on damages incurred when a debtor fails to make payments.

[0034] The "interest rate" item is an item that stores interest on a debt. The "debtor" item is an item that stores a person who owes a debt. The "debtor" item stores, for example, an owner ID. The "creditor" item is an item that stores a person who has the right to demand a specific action from a debtor. The "creditor" item stores, for example, a creditor ID. The "expected balance" item is an item that stores the balance of a debt.

[0035] A user of the system 1 can add and register a new record in the debt database 1015 or update the contents of a record registered in the debt database 1015 by operating the user terminal 20. Alternatively, the server 10 executes an analysis process (S400) described below, whereby a new record is added to the debt database 1015 or the contents of an existing record are updated. The analysis process will be described in detail later.

[0036] The creditor database 1016 is a database that stores information about debtors (hereinafter, also referred to as creditor data). As shown in Fig. 7, as an example, the creditor database 1016 has an item "creditor ID" and an item "address". Note that the creditor database 1016 may have items other than these, or may not have any of these.

[0037] The item "Creditor ID" is an item for storing an identifier for identifying a creditor registered in the creditor database 1016. The item "Address" is an item for storing information regarding the address of the creditor.

[0038] A user of the system 1 can add and register a new record in the creditor database 1016 or update the contents of a record registered in the creditor database 1016 by operating the user terminal 20. Alternatively, the server 10 executes an analysis process (S400) described below, whereby a new record is added to the creditor database 1016 or the contents of an existing record are updated. The analysis process will be described in detail later.

[0039] The shaping request 1014 is a request to have the large-scale language model M provided by the external server S output shaping data for a property described in the registry data based on the specified registry data. The shaping data is, for example, data in which information about a property described in the registry data is arranged in a specified order. The shaping data may also be, for example, data in which information about a property described in the registry data is arranged in an order according to the type of data and described in a specified data format. The shaping data may also be, for example, data in which information about a specified property is arranged in an order according to data corresponding to a database and described in a specified data format. More specifically, the shaping data is, for example, data in which information about a specified property is arranged in an order according to data corresponding to a database and data described in Jason format is converted into a data type called a dictionary type, object type, or the like. However, the format and data type of the shaping data are not limited to this example and can be set appropriately by the user. The registry data also includes the history of ownership of the property. In other words, the registry data includes the past and present owners. Therefore, the real estate data also includes information about the past and present owners.

[0040] The shaping request 1014 is, for example, a prompt (command sentence) input to the large-scale language model M, and can be specified in natural language. Specifically, the shaping request 1014 may be specified in the form of a sentence requesting a person, such as "organize the information in the registration data by title section (display of land), right section (area A), and right section (area B), and output in Jason format." The format of the shaping data is an example, and can be appropriately set by the user changing the shaping request. In this embodiment, the shaping request 1014 is stored in the storage unit 101, but is not limited to this example, and the server 10 may receive the shaping request 1014 input by the user to the user terminal 20.

[0041] <2.2. Configuration of the control unit 104 of the server 10> The control unit 104 of the server 10 includes, as functional units, a transmission / reception module 1041, an acquisition module 1042, a generation module 1043, and a data management module 1045. The control unit 104 executes an application program 1011 stored in the storage unit 101 to operate as each functional unit.

[0042] The transmission / reception module 1041 controls the process in which the server 10 transmits and receives signals to and from an external device (eg, the user terminal 20) in accordance with a communication protocol.

[0043] The acquisition module 1042 acquires registration data related to real estate registration. The registration data is data having information such as the address, identification information (e.g., real estate number), land area, owner, and share of the real estate property. As an example, the registration data holds information corresponding to each item of the property database 1013 in the storage unit 101. As another example, the registration data holds information corresponding to each item of the owner database 1012 in the storage unit 101. As another example, the registration data holds information corresponding to each item of the debt database 1015 in the storage unit 101. The format of the registration data may be a document format such as PDF, or may be an image format. The registration data may not have the items themselves as long as it has information related to each item. As an example, the registration data may be a certified copy of the registration (certificate of registered matters) related to the real estate property. Also, the registration data may be a data file obtained by scanning the certified copy of the registration book with a scanner. One piece of registration data may include information about one or more properties. The acquisition module 1042 acquires one or more pieces of registration data designated by the user.

[0044] The generation module 1043 generates shaping data based on the registration data using the large-scale language model M provided by the external server S. Specifically, the generation module 1043 transmits the registration data acquired by the acquisition module 1042 and the shaping request 1014 stored in the storage unit 101 to the transmission / reception module 1041, thereby transmitting the data to the external server S. In the external server S, the received registration data and the shaping request are input to the large-scale language model, and shaping data based on the registration data is output. The large-scale language model M does not analyze characters related to the items in the registration data, grasp what the items are, and shape the information. The large-scale language model M estimates what the information is from the arrangement of the character strings in the registration data, and generates shaping data based on the estimated information. The transmission / reception module 1041 receives the generated shaping data from the external server S.

[0045] In addition, the generation module 1043 may encrypt the registration data acquired by the acquisition module 1042 before transmitting the registration data to the external server S. As the encryption method, a shared key encryption method such as the Advanced Encryption Standard (AES) algorithm, a public key encryption method such as the Rivest-Shamir-Adleman (RSA) algorithm, or a hybrid encryption method using both of them can be appropriately adopted. In this case, the transmission / reception module 1041 transmits the encrypted registration data to the external server S. The external server S outputs the encrypted shaping data by inputting the encrypted registration data and a shaping request to the large-scale language model M. The generation module 1043 decrypts the encrypted shaping data. With such specifications, the registration data to be transmitted to the external server S and the shaping data to be output based on the registration data are encrypted, and when an external learning model is used, it is possible to prevent leakage of personal information described in the registration data.

[0046] The data management module 1045 stores data included in the shaping data in the storage unit 101. Specifically, the data management module 1045 stores, for example, property data, which is data related to a specific property, included in the shaping data, in the property database 1013 of the storage unit 101 (corresponding to the "first storage step" in the claims). The data management module 1045 also stores, for example, owner data, which is data related to an owner of a specific property, included in the shaping data, in the owner database 1012 of the storage unit 101 (corresponding to the "second storage step" in the claims). The data management module 1045 also stores debt data, which is data related to a debt related to a specific property, included in the shaping data, in the debt database 1015 of the storage unit 101. The data management module 1045 also stores creditor data, which is data related to a creditor, in the creditor database 1016 of the storage unit 101. Furthermore, the data management module 1045 associates the property data stored in the property database 1013, the owner data stored in the owner database 1012, the debt data stored in the debt database 1015, and the creditor data stored in the creditor database 1016. The processing of the data management module 1045 is executed by an analysis process (S400 / FIG. 9). The analysis process will be described in detail later.

[0047] <3. Configuration of User Terminal 20> As shown in FIG. 3, the user terminal 20 is an information processing device operated by a user who uses a service. The user terminal 20 may be, for example, a mobile terminal such as a smartphone or a tablet, or may be a stationary PC (Personal Computer) or a laptop PC. It may also be a wearable terminal such as an HMD (Head Mount Display) or a wristwatch-type terminal. The user terminal 20 may also be a multifunction device capable of executing at least one of the functions of copying, printing, scanning, and facsimile. The user terminal 20 may also be connectable to a multifunction device. The user terminal 20 includes a storage unit 211, a control unit 214, an input device 216, and an output device 218.

[0048] 3.1. Configuration of the storage unit 211 of the user terminal 20 The storage unit 211 of the user terminal 20 includes an application program 2111. The application program 2111 may be stored in advance in the storage unit 201, or may be configured to be downloaded from a web server operated by a service provider via a communication IF. The application program 2111 includes an application such as a web browser application. The application program 2111 includes an interpreter-type programming language such as JavaScript (registered trademark) that is executed on the web browser application stored in the user terminal 20.

[0049] 3.2. Configuration of the control unit 214 of the user terminal 20 The control unit 214 of the user terminal 20 includes, as functional units, an operation reception unit 2141, a transmission / reception unit 2142, and a notification control unit 2143. The control unit 214 executes an application program 2111 stored in the storage unit 211, whereby each functional unit is realized.

[0050] The operation receiving unit 2141 performs processing for receiving a user's operation input from the input device 216. For example, the operation receiving unit 2141 determines the type of operation, such as whether the operator's operation is a flick operation, a tap operation, or a drag (swipe) operation, based on information on the coordinates where the user touches the touch device 2165 with a finger or the like, and receives the operation.

[0051] The transmission / reception unit 2142 performs processing for the user terminal 20 to transmit and receive data to and from an external device such as the server 10 in accordance with a communication protocol.

[0052] The notification control unit 2143 notifies the user of various information by outputting various data to the output device 218. Specifically, the notification control unit 2143 causes the display 2181 to display data such as images, videos, and text to be notified to the user. In addition, the notification control unit 2143 causes the speaker 2182 to output an audio signal of the data to be notified to the user.

[0053] <3.3. Configuration of the input device 216 of the user terminal 20> The input device 216 of the user terminal 20 includes a camera 2161 , a microphone 2162 , a position information sensor 2163 , a motion sensor 2164 , and a touch device 2165 .

[0054] 3.4. Configuration of the output device 218 of the user terminal 20 The output device 218 of the user terminal 20 includes a display 2181 and a speaker 2182 .

[0055] <4. Operation of System 1> Each process of the system 1 will be described below.

[0056] <4.1. Overall operation> 8 and 9 are flowcharts showing an overall picture of the processing flow of the system 1. In step S110 shown in Fig. 8, the operation acceptance unit 2141 of the user terminal 20 accepts registration data from a user. As an example, the operation acceptance unit 2141 accepts a selection operation by the user to accept a selection of one or more pieces of registration data downloaded in advance to the user terminal 20.

[0057] In step S120, the transmitting / receiving unit 2142 of the user terminal 20 transmits the registry data selected by the user via the operation receiving unit 2141 to the server 10. In step S210, the transmitting / receiving module 1041 of the server 10 receives the registry data transmitted from the user terminal 20. Next, the acquiring module 1042 acquires the registry data received by the transmitting / receiving module 1041. The acquiring module 1042 further acquires a shaping request 1014 stored in the storage unit 101. As an example, the shaping request 1014 is a request to generate shaping data in which information about a property described in the registry data is organized in an order according to a database.

[0058] In step S220, the generating module 1043 encrypts the registration data acquired by the acquiring module 1042. As an example, the generating module 1043 generates the encrypted registration data using the AES algorithm.

[0059] In step S230, the generation module 1043 transmits the encrypted registration data and the shaping request to the external server S by transferring them to the transmission / reception module 1041. In step S310, the external server S receives the encrypted registration data and the shaping request.

[0060] In step S320, the external server S inputs the encrypted registration data and the shaping request to the large-scale language model M as a trained model, and causes the large-scale language model M to output the shaping data. In step S330, the external server S transmits the shaping data output by the large-scale language model M to the server 10. In step S240, the transmission / reception module 1041 of the server 10 receives the shaping data from the external server S.

[0061] In step S250, the generating module 1043 decrypts the registry data received from the external server S. As an example, the generating module 1043 decrypts the shaping data using the AES algorithm. FIG. 10 is a diagram illustrating a concept of a part of the decrypted shaping data D in a table. In FIG. 10, the shaping data D arranges information about a specific property in an order according to a database. In addition, in the shaping data D, for example, property data, owner data of the property, debt data, and creditor data are associated with each other. In the shaping data D, for example, a record is generated for each registry data. Note that the shaping data shown in FIG. 10 is only a part, and may include information other than that shown in FIG. 10.

[0062] In step S400 of Fig. 9, the shaped data is analyzed. In the analysis process (S400), the data management module 1045 executes a step of storing property data, owner data, debt data, and creditor data in a database, and a step of associating the property data, owner data, debt data, and creditor data described in the same record in the shaped data. The analysis process will be described in detail later.

[0063] In step S260, the transmission / reception module 1041 of the server 10 transmits the registration results of the property data, owner data, debt data, and creditor data in the memory unit 101 by the analysis process (S400) to the user terminal 20. In step S130, the transmission / reception unit 2142 of the user terminal 20 receives the registration results of the property data, owner data, debt data, and creditor data from the server 10. In step S140, the notification control unit 2143 of the user terminal 20 notifies the user of the registration results of the property data, owner data, debt data, and creditor data. As an example, the notification control unit 2143 displays the registration results on the display 2181.

[0064] <4.2. Analysis process flow> The flow of the analysis process (S400) will be described with reference to Figures 11 to 13. Figures 11 to 13 show an example in which the data management module 1045 stores property data in the property database 1013 and stores owner data in the owner database 1012.

[0065] In step S405 shown in Fig. 11, the data management module 1045 extracts property data and owner data from the decrypted shaped data. In the shaped data, for example, data corresponding to property data, owner data, debt data, and creditor data are arranged so as to be distinguishable by data position. The data management module 1045 repeats the processes of steps S410 to S480 shown below as many times as the number of records in the shaped data.

[0066] In step S410, the data management module 1045 determines whether or not the owner data extracted from a predetermined record (hereinafter, referred to as the record) of the shaping data has already been registered in the owner database 1012 of the storage unit 101 (i.e., whether or not a record corresponding to the owner data extracted from the shaping data exists in the owner database 1012), for example, based on the name and address of the owner. If the owner data extracted from the shaping data has already been registered in the owner database 1012 (Yes in step S410), step S420 shown in FIG. 12 is executed. On the other hand, if the owner data is not registered in the owner database 1012 (No in step S410), step S450 shown in FIG. 13 is executed.

[0067] Hereinafter, with reference to FIG. 12, a case will be described in which the owner data extracted from the corresponding record of the shaped data has already been registered in the owner database 1012.

[0068] 12, the data management module 1045 determines whether or not the property data in the record has already been registered in the property database 1013 of the storage unit 101 (i.e., whether or not a record corresponding to the property data in the record exists in the property database 1013). If the property data included in the shaped data has already been registered in the property database 1013 (Yes in step S420), S430 is executed. On the other hand, if the property data is not registered in the property database 1013 (No in step S420), step S425 is executed.

[0069] In step S430, the data management module 1045 determines whether the owner of the extracted property matches. Specifically, for example, the data management module 1045 refers to the owner database 1012 for the owner included in the shaping data, and determines whether the property stored in the item "Owned Real Estate" matches the property included in the shaping data. If the property matches (Yes in step S430), step S435 is executed. On the other hand, if the owner information does not match (No in step S430), step S440 is executed.

[0070] In step S435, the data management module 1045 updates the information in the property database 1013, and ends the analysis process for that record.

[0071] In step S440, the data management module 1045 changes the owner of the property based on the owner information in the record of the shaping data. Specifically, the data management module 1045 stores the property information included in the shaping data in the item "Owned Real Estate" in the owner database 1012 for the corresponding owner. This makes the corresponding owner the current final owner. Note that the property information is maintained as past owner information in the owner database 1012 of the owner who previously owned the property.

[0072] In the process of determining whether the owner matches in step S430, if the property is shared, the data management module 1045 also checks the owner's share. The data management module 1045 refers to the owner database 1012 for the owner included in the shaping data, and determines whether the property and share stored in the item "Owned Real Estate" match the property and share included in the shaping data. The data management module 1045 executes step S435 when both the property and the share match. On the other hand, if at least one of the property and the share does not match, the data management module 1045 executes step S440.

[0073] In step S425, the data management module 1045 registers the property data in the record of the shaped data in the property database 1013. Specifically, the data management module 1045 adds a record related to the property data to the property database 1013 and stores it therein.

[0074] In step S445, the data management module 1045 associates the record added to the property database 1013 with the owner data stored in the owner database 1012 based on the owner data in the record of the shaped data. Specifically, the data management module 1045 adds the item "Property ID" of the record added to the property database 1013 in step S425 to the item "Owned Real Estate" in the owner database 1012 of the corresponding owner. This associates the property data and owner data stored in the storage unit 101.

[0075] Next, with reference to FIG. 13, a case will be described in which the owner data extracted from the record of the shaped data is not registered in the owner database 1012.

[0076] In step S450 shown in FIG. 13, the data management module 1045 registers the owner data in the record in the owner database 1012. Specifically, the data management module 1045 adds and stores a record related to the owner data in the record in the owner database 1012. The data management module 1045 may perform a name matching process based on the owner data added to the owner database 1012. For example, when there is information that indicates the same owner, but the owner's name, address, or both are different, the data management module 1045 may match the information registered in the owner database 1012 with the newly registered information so that the information is unified with the latest information. The data management module 1045 determines that the newly stored information indicates the same owner as the registered information, for example, based on information acquired from other registration data, and performs a name matching process.

[0077] 13, data management module 1045 determines whether or not the property data in the record of the shaped data has already been registered in property database 1013 of storage unit 101. If the property data has already been registered in property database 1013 (Yes in step S460), step S470 is executed. On the other hand, if the property data has not been registered in property database 1013 (No in step S460), step S475 is executed.

[0078] In step S470, the data management module 1045 updates the owner of the property stored in the property database 1013 based on the owner information in the corresponding record of the shaping data. Specifically, the data management module 1045 extracts, for example, the owner associated with the property stored in the property database 1013, and updates the information about the property stored in the item "Owned Real Estate" in the owner database 1012 for the corresponding owner. In addition, if the property is shared, the share in the item "Owned Real Estate" in the owner database 1012 is updated.

[0079] In step S475, the data management module 1045 registers the property data in the record in question in the property database 1013. Specifically, the data management module 1045 adds a record relating to the property data in question to the property database 1013 for storage.

[0080] In step S480, the data management module 1045 associates the record added to the property database 1013 with the owner data stored in the owner database 1012 based on the owner data in the record. Specifically, the data management module 1045 adds the item "Property ID" of the record added to the property database 1013 in step S475 to the item "Owned real estate" in the owner database 1012 of the corresponding owner. This associates the property data and owner data stored in the storage unit 101.

[0081] The data management module 1045 performs an analysis process similar to those shown in Figs. 11 to 13, extracts debt data from the shaped data, and stores the extracted debt data in the debt database 1015. The data management module 1045 also performs an analysis process similar to those shown in Figs. 11 to 13, extracts creditor data from the shaped data, and stores the extracted creditor data in the creditor database 1016. The data management module 1045, for example, associates a debtor in the debt data managed in the debt database 1015 with an owner managed in the owner database 1012. The data management module 1045, for example, associates a creditor in the debt data managed in the debt database 1015 with creditor data managed in the creditor database 1016.

[0082] <5. Basic Hardware Configuration of Computer 90> 14 is a block diagram showing the basic hardware configuration of a computer 90. The computer 90 includes at least a processor 901, a main storage device 902, an auxiliary storage device 903, and a communication IF 991 (interface). These are electrically connected to each other by a communication bus 921.

[0083] The processor 901 is hardware for executing an instruction set described in a program, and is composed of an arithmetic unit, a register, a peripheral circuit, and the like.

[0084] The main memory device 902 is for temporarily storing programs, data to be processed by the programs, etc. For example, it is a volatile memory such as a DRAM (Dynamic Random Access Memory).

[0085] The auxiliary storage device 903 is a storage device for saving data and programs, such as a flash memory, a hard disk drive (HDD), a magneto-optical disk, a CD-ROM, a DVD-ROM, or a semiconductor memory.

[0086] The communication IF 991 is an interface for inputting and outputting signals for communicating with other computers via a network using a wired or wireless communication standard. The network is composed of the Internet, a LAN, various mobile communication systems constructed by wireless base stations, etc. For example, the network includes 3G, 4G, and 5G mobile communication systems, LTE (Long Term Evolution), and wireless networks (e.g., Wi-Fi (registered trademark)) that can be connected to the Internet through a predetermined access point. In the case of a wireless connection, the communication protocols include, for example, Z-Wave (registered trademark), ZigBee (registered trademark), Bluetooth (registered trademark), etc. In the case of a wired connection, the network also includes a network that is directly connected by a USB (Universal Serial Bus) cable or the like.

[0087] It should be noted that the computer 90 can be virtually realized by distributing all or part of each hardware configuration among multiple computers 90 and connecting them together via a network. In this way, the computer 90 is a concept that includes not only a computer 90 housed in a single housing or case, but also a virtualized computer system.

[0088] <6. Basic Functional Configuration of Computer 90> A description will now be given of the functional configuration of the computer realized by the basic hardware configuration of the computer 90. The computer at least comprises the functional units of a control unit, a storage unit, and a communication unit.

[0089] The functional units of the computer 90 can also be realized by distributing all or part of the functional units among multiple computers 90 connected to each other via a network. The computer 90 is a concept that includes not only a single computer 90 but also a virtualized computer system.

[0090] The control unit is realized by the processor 901 reading out various programs stored in the auxiliary storage device 903, expanding the programs in the main storage device 902, and executing processes according to the programs. The control unit can realize functional units that perform various information processing depending on the type of program. In this way, the computer is realized as an information processing device that performs information processing.

[0091] The storage unit is realized by a main storage device 902 and an auxiliary storage device 903. The storage unit stores data, various programs, and various databases. Furthermore, the processor 901 can secure a storage area corresponding to the storage unit in the main storage device 902 or the auxiliary storage device 903 in accordance with a program. Furthermore, the control unit can cause the processor 901 to execute processes of adding, updating, and deleting data stored in the storage unit in accordance with the various programs.

[0092] The term database refers to a relational database, which is used to manage sets of data called masters and tables in a tabular format structurally defined by rows and columns, by associating them with each other. In a database, a table is called a table or master, a column in a table is called a column, and a row in a table is called a record. In a relational database, relationships between tables and masters can be set and associated.

[0093] Usually, a column that serves as a primary key for uniquely identifying a record is set in each table and each master, but setting a primary key in a column is not essential. The control unit can cause the processor 901 to add, delete, or update records in a specific table or master stored in the storage unit according to various programs. Furthermore, by storing data, various programs, and various databases in the storage unit, it can be considered that the information processing device and information processing system according to the present disclosure have been manufactured.

[0094] In addition, the database and master in this disclosure may include any data structure (such as a list, a dictionary, an associative array, or an object) in which information is structurally defined. The data structure also includes data that can be considered as a data structure by combining data with a function, class, method, or the like written in any programming language.

[0095] The communication unit is realized by the communication IF 991. The communication unit realizes a function of communicating with other computers 90 via a network. The communication unit can receive information transmitted from other computers 90 and input the information to the control unit. The control unit can cause the processor 901 to execute information processing on the received information in accordance with various programs. In addition, the communication unit can transmit information output from the control unit to other computers 90.

[0096] <7. Summary> As described above, in this embodiment, the system 1 executes the following steps: an acquisition step (S110, S210) for acquiring registration data related to real estate registration; a generation step (S320) for generating shaped data based on the registration data using a trained model; a first storage step (S425, S475) for extracting property data, which is data related to the property, from the shaped data (S405) and storing the extracted property data in a memory; a second storage step (S450) for extracting owner data, which is data related to the owner, from the shaped data (S405) and storing the extracted owner data in a memory; and an association step (S440, S445, S470, S480) for associating the owner data and property data stored in the memory. With this configuration, the "context" of the registration data is determined by machine learning, the information is classified, and shaped data is generated, so that information can be acquired from the real estate certified copy with high accuracy, and information on the real estate certified copy can be efficiently managed.

[0097] Furthermore, in the first storage step and the second storage step, the control unit 104 stores the property data and the owner data in separate databases, which further improves the efficiency of data management.

[0098] The control unit 104 also executes a third storage step of extracting debt data, which is data related to debts, from the shaped data and storing the extracted debt data in memory, and a fourth storage step of extracting creditor data, which is data related to creditors, from the shaped data and storing the extracted creditor data in memory. In an association step, the control unit 104 associates the owner data, debt data, and creditor data stored in the memory. This makes it possible to manage debt information and creditor information as well, making it possible to more efficiently manage information obtained from the certified copy of real estate.

[0099] Furthermore, in the first, second, third and fourth storage steps, the control unit 104 stores the property data, the owner data, the debt data and the creditor data in separate databases, thereby further improving the efficiency of data management.

[0100] In addition, in the generation step, a shaping request for generating shaping data may be input to a large-scale language model M as a trained model, and the shaping data may be output from the large-scale language model M. With this configuration, it is possible to manage registration data using a large-scale language model trained using a large amount of parameters and high-level computational resources, thereby improving the efficiency of management operations.

[0101] The formatting request may be a request to generate formatted data in which data included in the acquired registration data is organized in an order according to the type of data, to the large-scale language model M. By configuring in this way, it is possible to create a data structure that is easy to store in a database.

[0102] The shaped data generated by the shaping step may have a record in which a specific property and the current and past owners of the property are described in association with each other, and the associating step may associate the owner data of the owner and the property data of the property described in the same record. With this configuration, it is possible to efficiently associate the owner data and the property data based on the shaped data generated by the generating step.

[0103] The shaped data generated by the shaping step may have records in which a specific property, a current or past owner of the property, a debt related to the property, and a creditor of the debt are described in association with each other, and the associating step may associate the owner data of the owner, the debt data of the debt, and the creditor data of the creditor, which are described in the same record. This makes it possible to efficiently associate the owner data, the debt data, and the creditor data based on the shaped data generated by the generating step.

[0104] In addition, in the generating step, the acquired registration data may be encrypted, the encrypted registration data may be input to a trained model as a trained model, and the shaped data output from the trained model may be decrypted. By adopting such specifications, it is possible to prevent personal information described in the registration data from being leaked when a trained model provided by an external server such as a publicly available large-scale language model M is used.

[0105] <8. Other embodiments> Although the embodiments to which the technical scope of the present application is applied have been described above, the present invention is not limited to the above contents.

[0106] For example, in the above embodiment, the large-scale language model M that is generally available through the external server S is used to generate shaping data based on the registration data, but the present invention is not limited to this embodiment. For example, a trained model that a user trains himself / herself may be stored in the storage unit 101 of the server 10, and the technical idea of ​​the present disclosure may be implemented using the trained model. With such specifications, the server 10 and the user terminal 20 of the system 1 can achieve the same effect as the above embodiment.

[0107] In the above embodiment, the registration data is encrypted (S220 in FIG. 8) and the shaping data is decrypted (S250 in FIG. 9), but encryption and decryption are not necessarily required. For example, as described above, when implementing the technical idea of ​​the present disclosure using a trained model stored in the storage unit 101 of the server 10, specifications may be made such that the registration data is not encrypted and the shaping data is not decrypted. By adopting such specifications, the processing of the system 1 can be simplified and the registration data can be managed more efficiently. In addition, when the large-scale language model M is designed such that input information is not used for learning, encryption and decryption are not necessarily required.

[0108] In the above embodiment, the shaping request 1014 is stored in the storage unit 101 of the server 10, but the present invention is not limited to this. For example, in step S210 of Fig. 8, the user terminal 20 may accept the registration data and the shaping request from the user at the same time. By adopting such a specification, it becomes easy to generate generated data based on the shaping request that reflects the detailed needs of the user.

[0109] In the above embodiment, the owner data is managed by the owner database 1012, and the property data is managed by the property database 1013, but the present invention is not limited to this embodiment. That is, the property data and the owner data may be managed in one database, or may be managed in three or more databases. As an example, a new database may be added to define the association between the owner database 1012 and the property database 1013.

[0110] In addition, in the above embodiment, the owner data is managed by the owner database 1012, the property data is managed by the property database 1013, the debt data is managed by the debt database 1015, and the creditor data is managed by the creditor database 1016, but the present invention is not limited to this embodiment. That is, these data may be managed in one database, or in three or more databases. As an example, a new database may be added to define the association between the owner database 1012, the debt database 1015, and the creditor database 1016.

[0111] In addition, in the above embodiment, an example was described in which owner data, property data, debt data, and creditor data are registered in the memory unit 101, but one or a combination of at least two or more of these may be registered in the memory unit 101.

[0112] In the above embodiment, the technical idea of ​​the present disclosure is applied to the management of real estate property and its owner based on the registration data such as a certified copy of real estate, but the present disclosure is not limited to this example. That is, the technical idea of ​​the present disclosure can be applied to the management of a uniquely identified object that is the subject of a specific right and the owner of the right. In this case, the acquisition module 1042 of the server 10 can acquire right holder data indicating the person who owns the right for the uniquely identified object instead of the registration data. In this way, the technical idea of ​​the present disclosure can be applied to situations other than the management of real estate property, and the same effect as the above embodiment can be obtained.

[0113] In addition, in the above embodiment, an example of a form in which each function is provided in the user terminal 20 or the server 10 is described, but this is not limited to this form, and some functions may be provided in the user terminal 20, the server 10, or both the user terminal 20 and the server 10 in a form different from the above embodiment.

[0114] For example, in the above embodiment, each step described as being executed by the user terminal 20 may be executed by the server 10, and each step described as being executed by the server 10 may be executed by the user terminal 20.

[0115] In addition, sharing of specific information via communication lines is mainly performed via a WAN such as the Internet, but between information processing devices, communication may also be performed only via short-range wireless communication such as Bluetooth (registered trademark) and infrared communication without using a WAN.

[0116] Furthermore, the present invention may be realized as a computer-readable non-transitory recording medium storing the above-mentioned program.

[0117] Various embodiments of the present invention have been described above, but these are presented as examples and are not intended to limit the scope of the invention. The novel embodiments can be implemented in various other forms, and various omissions, substitutions, and modifications can be made without departing from the spirit of the invention. The embodiments and modifications thereof are included in the scope and spirit of the invention, and are included in the scope of the invention and its equivalents described in the claims.

[0118] <9. Notes> The matters described in the above embodiments will be supplemented below.

[0119] (Appendix 1) A program for causing a computer having a processor and a memory to execute processing, the program causing the processor to execute the following steps: an acquisition step for acquiring registration data related to real estate registration; a generation step for generating shaped data based on the registration data using a trained model; a first storage step for extracting property data, which is data related to a property, from the shaped data and storing the extracted property data in a memory unit; a second storage step for extracting owner data, which is data related to the owner of the property, from the shaped data and storing the extracted owner data in a memory unit; and an association step for associating the owner data stored in the memory unit with the property data. (Appendix 2) The program according to claim 1, wherein in the first storing step and the second storing step, the property data and the owner data are stored in separate databases. (Appendix 3) A program described in Appendix 2, which causes a processor to execute a third storage step of extracting debt data, which is data regarding debt, from the formatted data and storing the extracted debt data in the memory unit, and a fourth storage step of extracting creditor data, which is data regarding creditors, from the formatted data and storing the extracted creditor data in the memory unit, and in an association step, associates the owner data, debt data, and creditor data stored in the memory unit. (Appendix 4) A program described in Appendix 3, in which in the first storage step, the second storage step, the third storage step, and the fourth storage step, the property data, the owner data, the debt data, and the creditor data are stored in separate databases. (Appendix 5) A program described in any one of (Appendix 1) to (Appendix 4), in which, in the generation step, a shaping request for generating shaping data is input to a large-scale language model as a trained model, and the large-scale language model is caused to output the shaping data. (Appendix 6) The formatting request is a request to the large-scale language model to generate formatted data in which the data contained in the acquired registration data is organized in an order according to the type of data (a program described in Appendix 6). (Appendix 7) A program described in any one of (Appendix 1) to (Appendix 6), in which the formatted data has a record in which a specific property is associated with the current and past owners of the property, and in an association step, the owner data of the owner and the property data of the property are associated in the same record. (Appendix 8) The formatted data has records in which a specific property, a current or past owner of the property, a debt related to the property, and a creditor of the debt are correspondingly recorded, and in an association step, the owner data of the owner, the debt data of the debt, and the creditor data of the creditor are associated with each other in the same record (a program described in Appendix 3). (Appendix 9) A program described in any one of (Appendix 1) to (Appendix 8), in which, in the generation step, the acquired registration data is encrypted, the encrypted registration data is input into a trained model, and the formatted data output from the trained model is decrypted. (Appendix 10) A method implemented by a computer having a processor and a memory, wherein the processor executes all of the steps performed in any of the inventions according to (Appendix 1) to (Appendix 9). (Appendix 11) An information processing device comprising a control unit and a memory unit, wherein the control unit executes all of the steps executed in the invention according to any one of (Appendix 1) to (Appendix 9). (Appendix 12) A system comprising means for executing all the steps performed in any of the inventions according to (Appendix 1) to (Appendix 9). [Explanation of symbols]

[0120] 1: system, 10: server, 20: user terminal, 90: computer, 101: memory unit, 104: control unit, 201: memory unit, 211: memory unit, 214: control unit, 216: input device, 218: output device, 901: processor, 902: main memory unit, 903: auxiliary memory unit, 921: communication bus, 1011: application program, 1012: owner database, 1013: property database, 1014: shaping request ,1041: transmission / reception module, 1042: acquisition module, 1043: generation module, 1045: data management module, 2111: application program, 2141: operation reception unit, 2142: transmission / reception unit, 2143: notification control unit, 2161: camera, 2162: microphone, 2163: position information sensor, 2164: motion sensor, 2165: touch device, 2181: display, 2182: speaker.

Claims

1. A program for causing a computer having a processor and a memory to execute a process, The processor, An acquisition step of acquiring registration data relating to real estate registration; a generation step of inputting the registry data and a command statement for outputting information about properties described in the registry data in an order corresponding to the type of data into a large-scale language model, which is a natural language model designed to execute multiple tasks of natural language processing, thereby causing the large-scale language model to generate formatted data in which information about properties described in the registry data is organized in an order corresponding to the type of data; a first storage step of extracting property data, which is data related to a property, from the shaped data and storing the extracted property data in a storage unit; a second storage step of extracting owner data relating to an owner of the property from the shaped data and storing the extracted owner data in the storage unit; an associating step of associating the owner data and the property data stored in the storage unit; A program that executes the following.

2. 2. The program according to claim 1, wherein said first storing step and said second storing step store said property data and said owner data in separate databases.

3. a third storage step of extracting debt data, which is data related to debt, from the shaped data and storing the extracted debt data in the storage unit; a fourth storage step of extracting creditor data, which is data related to creditors, from the shaped data and storing the extracted creditor data in the storage unit; causing the processor to execute 3. The program according to claim 2, wherein in said associating step, said owner data, said debt data and said creditor data stored in said storage unit are associated with each other.

4. 4. The program according to claim 3, wherein in the first storage step, the second storage step, the third storage step, and the fourth storage step, the property data, the owner data, the debt data, and the creditor data are stored in separate databases.

5. The said formatting data has a record in which a specific property is associated with the current and past owners of the property, 2. The program according to claim 1, wherein said associating step associates owner data of an owner and property data of a property described in the same record.

6. The formatted data includes a record in which a specific property, a current or past owner of the property, a debt related to the property, and a creditor of the debt are described in association with each other; 4. The program according to claim 3, wherein said associating step associates owner data of an owner, debt data of a debt, and creditor data of a creditor, all of which are described in the same record.

7. 2. The program according to claim 1, wherein the generating step encrypts the acquired registry data, inputs the encrypted registry data into the large-scale language model, and decrypts formatted data output from the large-scale language model.

8. A method implemented on a computer having a processor and a memory, the processor performing all of the steps performed in any one of claims 1 to 7.

9. 8. An information processing apparatus comprising a control unit and a storage unit, the control unit executing all steps executed in the invention according to any one of claims 1 to 7.

10. A system comprising means for executing all the steps performed in any one of claims 1 to 7.

Images