Method and system for constructing legal knowledge graph

Abstract

The invention relates to the technical field of knowledge graph construction, in particular to a legal knowledge graph construction method and system.The legal knowledge graph construction method comprises the steps that a legal knowledge graph to be constructed is divided into a plurality of hierarchies according to a preset hierarchy division rule, and each hierarchy comprises a plurality of logically-associated legal provisions, discriminants, laws and regulations and related instructions; and when a legal user initiates a query request, performing verification on a query condition and user identity information, calling a de-mixing algorithm, performing recovery processing on the knowledge graph of the mixed hierarchy, and remapping disordered hierarchy information into an original preset hierarchy structure. According to the method and the system, the legal knowledge information is stored in the database to display correct legal knowledge information, and only disordered hierarchical information is displayed even if the data is illegally leaked by hierarchically disassembling, randomly numbering and recombining and confusing the graph data, so that unauthorized recovery and abuse are prevented, and meanwhile, the retrieval experience and data integrity of legal users are guaranteed.

Description

Technical Field

[0001] The present invention relates to the technical field of knowledge graph construction, and in particular to a method and system for constructing a legal knowledge graph. Background Art

[0002] With the rapid development of the digital age, the trend of digitalization and networking of legal information is becoming increasingly obvious. A large number of legal provisions, precedents, regulations and related explanations are constructed into legal knowledge graphs to assist intelligent retrieval and decision support.

[0003] For example, in the prior art, Chinese patent publication number: CN118861311A discloses a legal knowledge graph automatic construction system and method, which relates to the field of knowledge graph technology. This legal knowledge graph automatic construction system and method, by setting a legal knowledge text data acquisition module, a legal knowledge text data processing module, a legal knowledge graph construction module, and a legal knowledge graph storage module, constructs a legal knowledge relationship extraction model, analyzes and classifies legal knowledge relationships, and constructs a legal knowledge graph. This can greatly improve the efficiency of legal workers and the public in acquiring and applying legal knowledge, reduce the time cost of information acquisition and processing, improve work efficiency and quality, calculate the legal compliance index of legal knowledge texts, help classify and organize text data, facilitate subsequent knowledge graph construction, help build a more accurate and complete legal knowledge graph, and improve the quality and efficiency of knowledge graphs.

[0004] However, existing legal knowledge graph construction methods usually directly integrate and present information at all levels, failing to effectively prevent the leakage of the complete knowledge structure when data is stolen or illegally obtained, which may lead to intellectual property infringement and information abuse. Summary of the Invention

[0005] The purpose of the present invention is to provide a method and system for constructing a legal knowledge graph. By performing hierarchical decomposition, random numbering, and reorganization and obfuscation on the graph data, even in the event of illegal data leakage, only chaotic hierarchical information is displayed, thereby preventing unauthorized restoration and abuse, while ensuring the retrieval experience and data integrity of legitimate users.

[0006] To this end, on one hand, the present invention provides a method for constructing a legal knowledge graph, which includes:

[0007] The legal knowledge graph to be constructed is divided into multiple levels according to the preset hierarchical division rules. Each level contains several logically related legal provisions, precedents, regulations and related explanations, and the node data in each level is classified and summarized;

[0008] Generate a unique random number for each node data in each level using a random numbering algorithm based on a dynamic seed;

[0009] Based on the random numbering, the node data of each level is split into several independent information fragments, each of which retains part of the data content and attributes related to the original node and removes the original hierarchical attribution information;

[0010] The information fragments are reorganized using a preset reconfiguration algorithm, and the information fragments are rearranged and combined according to a predetermined mixing rule to form a mixed-level knowledge graph;

[0011] When a legitimate user initiates a query request, the query conditions and user identity information are verified, the unmixing algorithm is called, the knowledge graph of the mixed hierarchy is restored, and the chaotic hierarchical information is remapped to the original preset hierarchical structure to display the correct legal knowledge information.

[0012] As a preferred technical solution for the construction method of the legal knowledge graph, the random numbering algorithm based on dynamic seeds includes:

[0013] Generate dynamic seeds based on user identity information, timestamp, and preset system parameters;

[0014] The dynamic seed and hash chain algorithm are used to operate on the node data in each level to generate unpredictable and unique random numbers.

[0015] As a preferred technical solution for the construction method of the legal knowledge graph, the splitting process of the node data at each level includes:

[0016] Extract key attribute information from each node data and separate it from auxiliary attribute information;

[0017] The separated information parts are formed into several information fragments, each of which contains only part of the data content and attributes, and each information fragment is independent of each other, stripping away the original hierarchical attribution information.

[0018] As a preferred technical solution for the construction method of the legal knowledge graph, the preset rematching algorithm adopts a rearrangement method based on chaos theory to randomly arrange and combine each information fragment according to predetermined mixing rules to form a mixed-level knowledge graph.

[0019] As a preferred technical solution for the construction method of the legal knowledge graph, the random numbering, information splitting and reconfiguration steps are all embedded with digital watermark information during execution. The digital watermark contains the generation time, processing sequence and version information for subsequent tracing and anti-tampering verification.

[0020] As a preferred technical solution for the construction method of the legal knowledge graph, the hybrid hierarchical knowledge graph generated after the information reorganization satisfies the condition that the logical associations between the levels and the node arrangement are in a chaotic state without authorization, and the original preset hierarchical structure cannot be restored through conventional retrieval means.

[0021] As a preferred technical solution for the construction method of the legal knowledge graph, the unmixing algorithm is based on preset keys and recovery rules, and only under legally authorized retrieval requests, the mixed information fragments are recombined according to the original hierarchical mapping relationship.

[0022] As a preferred technical solution for the method of constructing a legal knowledge graph, the method of constructing a legal knowledge graph also includes the steps of logging and monitoring each authorized retrieval behavior. The log records include query time, user identity, query conditions, and unmixing and recovery process information to support auditing and security analysis of access behavior.

[0023] On the other hand, the present invention further provides a legal knowledge graph construction system, which is applied to the legal knowledge graph construction method described in any of the above solutions, including:

[0024] An input module, used for receiving and preprocessing the legal knowledge data to be constructed;

[0025] A random numbering module, connected to the input module, is used to generate a unique random number based on a dynamic seed and perform random numbering processing on node data at each level;

[0026] A hierarchical division module, connected to the input module, is used to divide the legal knowledge data into multiple levels according to a preset hierarchical division rule, and classify and summarize the node data in each level;

[0027] An information splitting module, connected to the hierarchical division module, is used to split the randomly numbered node data into several independent information fragments, while stripping off the original hierarchical attribution information;

[0028] a reconfiguration module, connected to the hierarchical division module and the information splitting module respectively, for using a preset reconfiguration algorithm to recombine the information fragments according to a predetermined mixing rule to form a knowledge graph of a mixed hierarchy;

[0029] The authorized retrieval module is connected to the reconfiguration module and is used to restore the chaotic knowledge graph to the original preset hierarchical structure and display the correct legal knowledge information through identity authentication and calling the unmixing algorithm when a legitimate user initiates a query request.

[0030] The beneficial effects of the present invention are:

[0031] The legal knowledge graph construction method of the present invention utilizes technical means such as preset hierarchical division, random numbering based on dynamic seeds, information splitting and re-matching confusion to achieve effective protection of legal knowledge graph data.

[0032] In particular, in the legal knowledge graph construction method of the present invention, even if the graph data is illegally obtained, since the mixed hierarchical data is displayed after the information is split and reconfigured, the original logical associations and hierarchical structures are destroyed and it is difficult to restore them to a usable knowledge system, thereby reducing the risk of infringement and abuse.

[0033] In particular, in the legal knowledge graph construction method of the present invention, after a legitimate user initiates a query request and passes identity authentication, the system calls the unmixing algorithm to accurately restore the preset hierarchical structure, ensuring that the correct legal knowledge information is displayed and meeting actual application needs.

[0034] In particular, the legal knowledge graph construction method of the present invention enhances the security and unpredictability of data through dynamic random numbering and hybrid recombination technology, and effectively improves the technical barriers of the legal knowledge graph in terms of data security and anti-theft.

[0035] In particular, the legal knowledge graph construction method of the present invention takes into account the balance between data security protection and legal information retrieval, which not only prevents intellectual property infringement but also ensures users' efficient and accurate access to legal knowledge. It has significant application value and promotion prospects. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] Figure 1 Flowchart of a method for constructing a legal knowledge graph in an embodiment of the present invention;

[0037] Figure 2 This is a structural block diagram of the legal knowledge graph construction system in an embodiment of the present invention. DETAILED DESCRIPTION

[0038] The technical solution of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the embodiments described are only some embodiments of the present invention, not all embodiments. All other embodiments obtained by ordinary technicians in this field based on the embodiments of the present invention without making any creative efforts shall fall within the scope of protection of the present invention.

[0039] In the description of the present invention, it should be noted that, unless otherwise expressly specified or limited, the terms "mounted," "connected," and "connected" should be understood in a broad sense. For example, they may refer to fixed, detachable, or integral connections; mechanical or electrical connections; direct or indirect connections through an intermediate medium; and internal communication between two components. Those skilled in the art will understand the specific meanings of the above terms in the present invention based on the specific circumstances.

[0040] The following describes embodiments of the present invention in detail. Examples of the embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals throughout represent the same or similar elements or elements having the same or similar functions. The embodiments described below with reference to the accompanying drawings are exemplary and are intended only to explain the present invention and are not to be construed as limiting the present invention.

[0041] like Figure 1 As shown, the present invention provides a method for constructing a legal knowledge graph, which includes:

[0042] Step S1: Divide the legal knowledge graph to be constructed into multiple levels according to the preset hierarchical division rules. Each level contains several logically related legal provisions, precedents, regulations and related explanations, and classifies and summarizes the node data in each level.

[0043] Step S2: Generate a unique random number for each node data in each level using a random numbering algorithm based on a dynamic seed;

[0044] Step S3: Based on the random numbering, the node data of each level is split into several independent information fragments, each of which retains part of the data content and attributes related to the original node and removes the original hierarchical attribution information;

[0045] Step S4: Reorganize the information fragments using a preset reconfiguration algorithm, rearrange and combine the information fragments according to a predetermined mixing rule to form a knowledge graph of a mixed level;

[0046] Step S5: When a legitimate user initiates a query request, the query conditions and user identity information are verified, the unmixing algorithm is called, the mixed hierarchical knowledge graph is restored, and the chaotic hierarchical information is remapped to the original preset hierarchical structure to display the correct legal knowledge information.

[0047] In the above embodiment, effective protection of legal knowledge graph data is achieved by using technical means such as preset hierarchical division, random numbering based on dynamic seeds, information splitting and re-matching obfuscation. In the legal knowledge graph construction method, even if the graph data is illegally obtained, since the mixed hierarchical data is displayed after information splitting and re-matching, the original logical associations and hierarchical structures are destroyed, and it is difficult to restore them to a usable knowledge system, thereby reducing the risk of infringement and abuse. After the legitimate user initiates a query request and passes the identity authentication, the system calls the unmixing algorithm to accurately restore the preset hierarchical structure, ensuring that the correct legal knowledge information is displayed to meet the actual application needs. Through dynamic random numbering and hybrid reorganization technology, the security and unpredictability of the data are enhanced, and the technical barriers of the legal knowledge graph in data security and anti-theft are effectively improved.

[0048] Specifically, the random numbering algorithm based on dynamic seeds includes:

[0049] Generate dynamic seeds based on user identity information, timestamp, and preset system parameters;

[0050] The dynamic seed and hash chain algorithm are used to operate on the node data in each level to generate unpredictable and unique random numbers. In detail, the unique identification and security protection of node data are achieved through a random numbering algorithm based on dynamic seeds. Specifically, the algorithm uses user identity information, timestamps, and preset system parameters to generate dynamic seeds, so that each generated seed is random and timely, and then uses the hash chain algorithm to operate on the node data in each level. This process ensures that the generated random numbers are not only unpredictable, but also unique for each node in the same system, thereby preventing external attackers from restoring the original data structure or cracking the data mapping relationship through reverse deduction. Through this dynamic random numbering mechanism, a high data protection barrier is formed in the initial stage of the construction of the legal knowledge graph, which improves the overall security and data privacy protection capabilities of the system, and also provides a reliable foundation for subsequent information splitting and mixed reorganization.

[0051] Specifically, the splitting process of node data at each level includes:

[0052] Extract key attribute information from each node data and separate it from auxiliary attribute information;

[0053] The separated parts of information are formed into several information fragments, each of which contains only part of the data content and attributes, and each information fragment is independent of each other, stripping off the original hierarchical attribution information. In detail, the steps of splitting the node data at each level realize the partial and fragmented processing of the data content by extracting key attribute information from each node data and separating it from the auxiliary attribute information. The specific operation is to divide the data with complete semantics and logical associations into several independent information fragments, each of which contains only part of the data content and attributes, and deliberately stripping off the original hierarchical attribution information. The principle of this is to make it impossible to fully present the overall logic and hierarchical relationship of the legal knowledge graph in a single information fragment, so that even if the information fragment is illegally obtained, it cannot directly constitute a knowledge graph with complete semantics. This splitting strategy effectively improves data security, prevents the leakage and illegal restoration of sensitive legal information, and lays the foundation for the subsequent restoration of the original structure through authorized retrieval.

[0054] On the basis of the above-mentioned embodiment, the preset rematching algorithm adopts a rearrangement method based on chaos theory to randomly arrange and combine each information fragment according to a predetermined mixing rule to form a mixed-level knowledge graph. In detail, chaos theory has the characteristics of high uncertainty and sensitivity to initial conditions. Its application in this method can significantly destroy the continuity and logical association of the original hierarchical structure, making the reorganized mixed-level knowledge graph appear chaotic and disordered without authorization. The effect is that even if the data is illegally stolen, the original preset hierarchical structure and logical relationship cannot be reconstructed through conventional retrieval means, thereby effectively preventing the infringement of intellectual property rights and the abuse of sensitive information, while ensuring that the system can correctly restore and display legal knowledge content under legal authorization.

[0055] Specifically, during the execution of the random numbering, information splitting and re-matching steps, digital watermark information is embedded. The digital watermark contains the generation time, processing sequence and version information for subsequent tracing and anti-tampering verification. Embedding digital watermark information in the random numbering, information splitting and re-matching steps is an important means for this embodiment to further enhance data integrity and tamper-proof capabilities. Digital watermarks usually contain generation time, processing sequence and version information. By embedding these tamper-proof information in each data fragment or re-assembly process, a strong basis can be provided for subsequent tracing and verification of the data. The principle is to use watermarks as data verification and traceability tools to ensure that any illegal modifications to the data content can be discovered in a timely manner, thereby improving the security protection level of the system. This measure not only provides important assistance for the recovery of legitimate data, but also provides data support for system security audits and anomaly detection, effectively preventing information tampering and forgery.

[0056] Specifically, the hybrid hierarchical knowledge graph generated after the information reorganization is in a chaotic state with its logical associations between levels and node arrangements without authorization, and the original preset hierarchical structure cannot be restored through conventional retrieval means. The hybrid hierarchical knowledge graph generated after the information reorganization is in a chaotic state with its logical associations between levels and node arrangements without authorization, forming a chaotic state. The principle is that through random numbering, information splitting and re-matching based on chaos theory, the original logical structure is destroyed, making it impossible for illegally obtained data to restore the original preset hierarchical structure through conventional retrieval tools or reverse engineering methods. In effect, this hybrid reorganization strategy effectively improves the security of the data. Even if the data is leaked, its display content cannot meet the normal use requirements of users, thereby preventing the occurrence of illegal data utilization and infringement to a certain extent, and providing an obvious protection barrier for the legal and authorized retrieval of data.

[0057] Specifically, the demixing algorithm is based on preset keys and recovery rules, and only under legally authorized retrieval requests, the mixed information fragments are recombined according to the original hierarchical mapping relationship. The principle of the above embodiment is to use keys and rules as an "unlocking" mechanism, so that only users who have been authenticated and have corresponding permissions can obtain the complete hierarchical structure after recovery. This method ensures the switching between the "hidden" and "public" states of the data, that is, in unauthorized situations, the data always remains in a confused state and cannot be recovered; under legal requests, the system can automatically call the demixing algorithm to recombine the information fragments according to the original mapping relationship, and restore a complete and logically rigorous legal knowledge graph. This not only ensures the security of data during transmission and storage, but also provides efficient and accurate query services for legal users.

[0058] Specifically, the method for constructing the legal knowledge graph also includes the steps of logging and monitoring each authorized retrieval behavior, and the log records include query time, user identity, query conditions, and de-mixing and recovery process information to support auditing and security analysis of access behaviors. Logging and monitoring each authorized retrieval behavior is an important measure to ensure system security and traceability. Specific operations include recording information such as query time, user identity, query conditions, and de-mixing and recovery process. These log information constitute a complete access audit chain. The principle is that by comprehensively recording and monitoring user operations, abnormal access behaviors can be discovered in real time, and an effective basis can be provided for subsequent tracing and accountability when security incidents occur. In effect, this measure not only improves the transparency and security of the system, but also provides data support for system administrators to timely discover and prevent potential security threats, and effectively maintain the overall stability and data security of the legal knowledge graph construction system.

[0059] On the other hand, the present invention further provides a legal knowledge graph construction system, which is applied to the legal knowledge graph construction method described in any of the above solutions, including:

[0060] An input module, used for receiving and preprocessing the legal knowledge data to be constructed;

[0061] A random numbering module, connected to the input module, is used to generate a unique random number based on a dynamic seed and perform random numbering processing on node data at each level;

[0062] A hierarchical division module, connected to the input module, is used to divide the legal knowledge data into multiple levels according to a preset hierarchical division rule, and classify and summarize the node data in each level;

[0063] An information splitting module, connected to the hierarchical division module, is used to split the randomly numbered node data into several independent information fragments, while stripping off the original hierarchical attribution information;

[0064] a reconfiguration module, connected to the hierarchical division module and the information splitting module respectively, for using a preset reconfiguration algorithm to recombine the information fragments according to a predetermined mixing rule to form a knowledge graph of a mixed hierarchy;

[0065] The authorized retrieval module is connected to the reconfiguration module and is used to restore the chaotic knowledge graph to the original preset hierarchical structure and display the correct legal knowledge information through identity authentication and calling the unmixing algorithm when a legitimate user initiates a query request.

[0066] The flowcharts and block diagrams in the accompanying drawings illustrate the possible architectures, functions and operations of the devices, methods and computer program products according to various embodiments of the present application. In this regard, each box in the flowchart or block diagram can represent a module, program segment or part of the code, which contains one or more executable instructions for implementing the specified logical functions. It should also be noted that in some alternative implementations, the functions marked in the boxes can also occur in an order different from that marked in the accompanying drawings. For example, two boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram and / or flowchart, as well as the combination of boxes in the block diagram and / or flowchart, can be implemented using a dedicated hardware-based device that performs the specified function or operation, or can be implemented using a combination of dedicated hardware and computer instructions.

[0067] Obviously, the above embodiments of the present invention are merely examples for the purpose of clearly illustrating the present invention, and are not intended to limit the embodiments of the present invention. A person skilled in the art would be able to make other variations or modifications based on the above description. It is not necessary and impossible to enumerate all embodiments here. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the present invention shall be included within the scope of protection of the claims of the present invention.

Claims

1. A method for constructing a legal knowledge graph, characterized in that: include: The legal knowledge graph to be constructed is divided into multiple levels according to the preset hierarchical division rules. Each level contains several logically related legal provisions, precedents, regulations and related explanations, and the node data in each level is classified and summarized; Generate a unique random number for each node data in each level using a random numbering algorithm based on a dynamic seed; Based on the random numbering, the node data of each level is split into several independent information fragments, each of which retains part of the data content and attributes related to the original node and removes the original hierarchical attribution information; The information fragments are reorganized using a preset reconfiguration algorithm, and the information fragments are rearranged and combined according to a predetermined mixing rule to form a mixed-level knowledge graph; When a legitimate user initiates a query request, the query conditions and user identity information are verified, the unmixing algorithm is called, the knowledge graph of the mixed hierarchy is restored, and the chaotic hierarchical information is remapped to the original preset hierarchical structure to display the correct legal knowledge information.

2. The method for constructing a legal knowledge graph according to claim 1, characterized in that: The dynamic seed-based random numbering algorithm includes: Generate dynamic seeds based on user identity information, timestamp, and preset system parameters; The dynamic seed and hash chain algorithm are used to operate on the node data in each level to generate unpredictable and unique random numbers.

3. The method for constructing a legal knowledge graph according to claim 1, characterized in that: The splitting process of node data at each level includes: Extract key attribute information from each node data and separate it from auxiliary attribute information; The separated information parts are formed into several information fragments, each of which contains only part of the data content and attributes, and each information fragment is independent of each other, stripping away the original hierarchical attribution information.

4. The method for constructing a legal knowledge graph according to claim 1, characterized in that: The preset rematching algorithm adopts a rearrangement method based on chaos theory to randomly arrange and combine each information fragment according to a predetermined mixing rule to form a knowledge graph of a mixed level.

5. The method for constructing a legal knowledge graph according to claim 4, characterized in that: During the execution of the random numbering, information splitting and re-assignment steps, digital watermark information is embedded. The digital watermark contains generation time, processing sequence and version information for subsequent tracing and anti-tampering verification.

6. The method for constructing a legal knowledge graph according to claim 2, characterized in that: The hybrid hierarchical knowledge graph generated after the information reorganization is in a chaotic state with respect to the logical associations and node arrangements between the hierarchies without authorization, and the original preset hierarchical structure cannot be restored through conventional retrieval means.

7. The method for constructing a legal knowledge graph according to claim 1, characterized in that: The demixing algorithm is based on a preset key and recovery rule, and only under a legally authorized retrieval request, the mixed information fragments are reassembled according to the original hierarchical mapping relationship.

8. The method for constructing a legal knowledge graph according to claim 1, characterized in that: The method for constructing the legal knowledge graph also includes the steps of logging and monitoring each authorized retrieval behavior, wherein the log records include query time, user identity, query conditions, and de-mixing and recovery process information to support auditing and security analysis of access behavior.

9. A system for constructing a legal knowledge graph, characterized in that: The method for constructing a legal knowledge graph as described in any one of claims 1 to 8 comprises: An input module, used for receiving and preprocessing the legal knowledge data to be constructed; A random numbering module, connected to the input module, is used to generate a unique random number based on a dynamic seed and perform random numbering processing on node data at each level; A hierarchical division module, connected to the input module, is used to divide the legal knowledge data into multiple levels according to a preset hierarchical division rule, and classify and summarize the node data in each level; An information splitting module, connected to the hierarchical division module, is used to split the randomly numbered node data into several independent information fragments, while stripping off the original hierarchical attribution information; a reconfiguration module, connected to the hierarchical division module and the information splitting module respectively, for using a preset reconfiguration algorithm to recombine the information fragments according to a predetermined mixing rule to form a knowledge graph of a mixed hierarchy; The authorized retrieval module is connected to the reconfiguration module and is used to restore the chaotic knowledge graph to the original preset hierarchical structure and display the correct legal knowledge information through identity authentication and calling the unmixing algorithm when a legitimate user initiates a query request.

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