Intelligent law dynamic cooperation system based on hierarchical legal knowledge graph

Abstract

The invention belongs to the technical field of computers, and particularly relates to a smart law dynamic coordination system based on a hierarchical legal knowledge graph, comprising a data acquisition unit which supports acquisition of various types of law data, including but not limited to contract documents, mails, voice calls, video conference records, legal image data and the like, structured conversion of unstructured data is realized by adopting CR and ASR technologies; through cooperation of a data acquisition unit, a multi-modal data center module, a data preprocessing module, a quantum encryption security module, a multi-modal data fusion unit, a multi-language intelligent processing module, a dynamic optimization module, a real-time updating module, an intelligent risk assessment module and a user management module, data collection, assessment, screening and encryption are realized. According to the invention, the system achieves the powerful functions, improves the collection and analysis of legal affair data, and is more practical.

Description

Technical Field

[0001] The present invention belongs to the field of computer technology, and in particular relates to an intelligent legal dynamic collaboration system based on a hierarchical legal knowledge graph. Background Art

[0002] With the development of network informatization, the legal work of the court also needs to change from traditional paper file management to digital file management, and digitize the document materials from case filing to case closing. In the case filing stage, through digital information collection, the digitization of case filing materials can be quickly realized.

[0003] In the existing technology, although knowledge graph technology has been applied to the legal field, it is mostly flat in structure, has not formed a hierarchical knowledge system, and has not been deeply integrated with the legal process. It cannot meet the needs of intelligent decision-making and process control in dynamic collaboration scenarios. In view of this, we propose an intelligent legal dynamic collaboration system based on a hierarchical legal knowledge graph. Summary of the Invention

[0004] The purpose of the present invention is to address the above-mentioned technical problems and provide an intelligent legal dynamic collaboration system based on a hierarchical legal knowledge graph to solve the problems raised in the above-mentioned background technology.

[0005] In view of this, the present invention provides a smart legal affairs dynamic collaboration system based on a hierarchical legal knowledge graph, including:

[0006] The data collection unit supports the collection of various types of legal data, including but not limited to contract documents, emails, voice calls, video conference records, legal imaging materials, etc., and uses CR and ASR technologies to achieve structured conversion of unstructured data;

[0007] A multimodal data middleware module, including a heterogeneous data fusion engine and a blockchain data safe, is used to achieve intelligent collection, semantic conversion, and secure sharing of multi-source legal data;

[0008] The data preprocessing module performs cleaning operations such as deduplication, error correction, and format conversion on the collected data. It also fills missing values and processes outliers to ensure data accuracy and consistency. It performs preprocessing operations such as format unification and missing value filling to improve data quality. It uses natural language processing technology to preprocess text data through word segmentation, part-of-speech tagging, named entity recognition, etc. to extract key information.

[0009] Quantum encryption security module, used to implement quantum encryption transmission and storage of legal data to ensure data security;

[0010] The multimodal data fusion unit uses deep learning and other technologies to fuse different types of data, build a unified data representation, and explore the potential connections and value between data;

[0011] The multilingual intelligent processing module, consisting of a legal terminology translation library, an optimized neural machine translation model, and a multilingual semantic parsing unit, enables accurate translation and in-depth analysis of multilingual legal documents;

[0012] The dynamic optimization module is equipped with an environmental perception and data acquisition unit, a reinforcement learning agent, and an optimization decision execution unit, which can dynamically optimize the system process based on real-time environmental information;

[0013] Real-time update module, including legal knowledge source monitoring unit, knowledge extraction and integration unit, knowledge push and application unit, to ensure that the system obtains and applies the latest legal knowledge in a timely manner;

[0014] Dynamic optimization module, through the reinforcement learning agent of the dynamic optimization module through continuous trial and error and learning, optimizes the strategy according to environmental feedback, and realizes autonomous dynamic adjustment of system processes;

[0015] The intelligent risk assessment module includes a legal knowledge graph construction submodule, a risk assessment submodule, and an intelligent retrieval and recommendation submodule, which is used to provide legal knowledge management, risk assessment, and intelligent decision-making assistance;

[0016] The user management module includes a user authentication and authorization sub-module, a user behavior analysis sub-module, and a user feedback and improvement sub-module.

[0017] In the above technical solution, further, the quantum encryption security module includes a quantum key distribution unit, a data encryption and decryption unit, and a security authentication and access control unit. The quantum encryption security module adopts the principle of quantum entanglement to distribute quantum keys and uses a quantum encryption algorithm to encrypt data.

[0018] In the above technical solution, further, the multimodal data processing module adopts OCR optical character recognition technology, ASR speech recognition technology and deep learning algorithm to realize the collection and fusion of structured, semi-structured and unstructured data.

[0019] In the above technical solution, further, the real-time update module can monitor multiple legal knowledge sources in real time, automatically extract and integrate new knowledge, and push and apply it according to user needs and business scenarios. The real-time update module can monitor that the country where the case is located has newly promulgated a legal provision related to commercial disputes. The knowledge extraction and integration unit quickly extracts key content and integrates it into the system knowledge system. The knowledge push and application unit pushes the legal provision to all personnel involved in case handling, and automatically applies new knowledge in case analysis, litigation document writing and other links to ensure that case handling complies with the latest legal regulations.

[0020] In the above technical solution, further, the legal knowledge graph construction submodule of the intelligent risk assessment module integrates laws and regulations, judicial interpretations, judicial cases and academic literature to construct a legal knowledge graph containing legal concepts, legal relations and legal rules.

[0021] In the above technical solution, further, the user authentication and authorization submodule: adopts a multi-factor authentication method to ensure the authenticity and legitimacy of the user identity, allocates different operation permissions according to user roles and business needs, and realizes fine-grained permission control.

[0022] In the above technical solution, further, the user behavior analysis submodule: records the user's operating behavior in the system, uses big data analysis technology to mine and analyze user behavior, builds user portraits, understands user needs and preferences, and provides users with personalized services and recommendations.

[0023] In the above technical solution, further, the user feedback and improvement submodule: collects user feedback on system functions, usage experience, etc., handles user problems and suggestions in a timely manner, and continuously optimizes system functions and interface design based on user feedback to improve user satisfaction.

[0024] The beneficial effects of the present invention are:

[0025] This involves an intelligent legal dynamic collaboration system based on a hierarchical legal knowledge graph. By setting up a data acquisition unit, a multimodal data middle-end module, a data preprocessing module, a quantum encryption security module, a multimodal data fusion unit, a multilingual intelligent processing module, a dynamic optimization module, a real-time update module, an intelligent risk assessment module and a user management module, it realizes the collection, evaluation, screening, encryption, storage and translation of data, thereby realizing the powerful functions of this system, improving the collection and analysis of legal data, and being more practical. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] Figure 1 It is one of the system module diagrams of the present invention;

[0027] Figure 2 This is the second system module diagram of the present invention;

[0028] Figure 3 This is the third system module diagram of the present invention DETAILED DESCRIPTION

[0029] The following will be combined with the accompanying drawings in the embodiments of this application to clearly describe the technical solutions in the embodiments of this application. Obviously, the embodiments described are part of the embodiments of this application, not all of the embodiments. Based on the embodiments in this application, all other embodiments obtained by ordinary technicians in this field are within the scope of protection of this application.

[0030] In the description of this application, it should be noted that the terms used herein are only for the purpose of describing specific embodiments and are not intended to limit the exemplary embodiments according to this application. For ease of description, the dimensions of the various parts shown in the drawings are not drawn according to the actual proportional relationship. Technologies, methods and equipment known to ordinary technicians in the relevant fields may not be discussed in detail, but where appropriate, the technologies, methods and equipment should be considered as part of the authorization specification. In all examples shown and discussed here, any specific values should be interpreted as merely exemplary and not as limitations. Therefore, other examples of the exemplary embodiments may have different values. It should be noted that similar numbers and letters represent similar items in the following figures, so once an item is defined in one figure, it does not need to be further discussed in subsequent figures.

[0031] It should be noted that, in the present application, the terms "comprise", "include" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device comprising a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, an element defined by the statement "comprises a ..." does not exclude the presence of other identical elements in the process, method, article or device comprising the element. In addition, it should be pointed out that the scope of the methods and devices in the embodiments of the present application is not limited to performing functions in the order shown or discussed, and may also include performing functions in a substantially simultaneous manner or in the opposite order according to the functions involved. For example, the described method may be performed in an order different from that described, and various steps may also be added, omitted, or combined. In addition, the features described with reference to certain examples may be combined in other examples.

[0032] Example 1:

[0033] See also Figure 1-Figure 3As shown, this embodiment provides an intelligent legal dynamic collaboration system based on a hierarchical legal knowledge graph.

[0034] include:

[0035] The data collection unit supports the collection of various types of legal data, including but not limited to contract documents, emails, voice calls, video conference records, legal imaging materials, etc., and uses CR and ASR technologies to achieve structured conversion of unstructured data;

[0036] A multimodal data middleware module, including a heterogeneous data fusion engine and a blockchain data safe, is used to achieve intelligent collection, semantic conversion, and secure sharing of multi-source legal data;

[0037] The data preprocessing module performs cleaning operations such as deduplication, error correction, and format conversion on the collected data. It also fills missing values and processes outliers to ensure data accuracy and consistency. It performs preprocessing operations such as format unification and missing value filling to improve data quality. It uses natural language processing technology to preprocess text data through word segmentation, part-of-speech tagging, named entity recognition, etc. to extract key information.

[0038] Quantum encryption security module, used to implement quantum encryption transmission and storage of legal data to ensure data security;

[0039] The multimodal data fusion unit uses deep learning and other technologies to fuse different types of data, build a unified data representation, and explore the potential connections and value between data;

[0040] The multilingual intelligent processing module, consisting of a legal terminology translation library, an optimized neural machine translation model, and a multilingual semantic parsing unit, enables accurate translation and in-depth analysis of multilingual legal documents;

[0041] The dynamic optimization module is equipped with an environmental perception and data acquisition unit, a reinforcement learning agent, and an optimization decision execution unit, which can dynamically optimize the system process based on real-time environmental information;

[0042] Real-time update module, including legal knowledge source monitoring unit, knowledge extraction and integration unit, knowledge push and application unit, to ensure that the system obtains and applies the latest legal knowledge in a timely manner;

[0043] Dynamic optimization module, through the reinforcement learning agent of the dynamic optimization module through continuous trial and error and learning, optimizes the strategy according to environmental feedback, and realizes autonomous dynamic adjustment of system processes;

[0044] The intelligent risk assessment module includes a legal knowledge graph construction submodule, a risk assessment submodule, and an intelligent retrieval and recommendation submodule, which is used to provide legal knowledge management, risk assessment, and intelligent decision-making assistance;

[0045] The user management module includes a user authentication and authorization sub-module, a user behavior analysis sub-module, and a user feedback and improvement sub-module.

[0046] Example 2:

[0047] This embodiment provides an intelligent legal dynamic collaboration system based on a hierarchical legal knowledge graph. In addition to the technical solutions of the above embodiments, it also has the following technical features.

[0048] Among them, the quantum encryption security module includes a quantum key distribution unit, a data encryption and decryption unit, and a security authentication and access control unit. The quantum encryption security module uses the principle of quantum entanglement to distribute quantum keys and uses quantum encryption algorithms to encrypt data.

[0049] Example 3:

[0050] This embodiment provides an intelligent legal dynamic collaboration system based on a hierarchical legal knowledge graph. In addition to the technical solutions of the above embodiments, it also has the following technical features.

[0051] in,

[0052] The multimodal data processing module uses OCR optical character recognition technology, ASR speech recognition technology and deep learning algorithms to realize the collection and integration of structured, semi-structured and unstructured data.

[0053] Example 4:

[0054] This embodiment provides an intelligent legal dynamic collaboration system based on a hierarchical legal knowledge graph. In addition to the technical solutions of the above embodiments, it also has the following technical features.

[0055] Among them, the real-time update module can monitor multiple legal knowledge sources in real time, automatically extract and integrate new knowledge, and push and apply it according to user needs and business scenarios. The real-time update module can monitor that the country where the case is located has newly promulgated a legal provision related to commercial disputes. The knowledge extraction and integration unit quickly extracts key content and integrates it into the system knowledge system. The knowledge push and application unit pushes the legal provision to all personnel involved in case handling, and automatically applies new knowledge in case analysis, litigation document writing and other links to ensure that case handling complies with the latest legal regulations.

[0056] Example 5:

[0057] This embodiment provides an intelligent legal dynamic collaboration system based on a hierarchical legal knowledge graph. In addition to the technical solutions of the above embodiments, it also has the following technical features.

[0058] Among them, the legal knowledge graph construction sub-module of the intelligent risk assessment module integrates laws and regulations, judicial interpretations, judicial cases and academic literature to construct a legal knowledge graph containing legal concepts, legal relations and legal rules.

[0059] Example 6:

[0060] This embodiment provides an intelligent legal dynamic collaboration system based on a hierarchical legal knowledge graph. In addition to the technical solutions of the above embodiments, it also has the following technical features.

[0061] Among them, the user authentication and authorization submodule: adopts multi-factor authentication to ensure the authenticity and legitimacy of user identity, assigns different operation permissions according to user roles and business needs, and realizes fine-grained permission control

[0062] Example 7:

[0063] This embodiment provides an intelligent legal dynamic collaboration system based on a hierarchical legal knowledge graph. In addition to the technical solutions of the above embodiments, it also has the following technical features.

[0064] Among them, the user behavior analysis sub-module: records the user's operating behavior in the system, uses big data analysis technology to mine and analyze user behavior, builds user portraits, understands user needs and preferences, and provides users with personalized services and recommendations.

[0065] Example 7:

[0066] This embodiment provides an intelligent legal dynamic collaboration system based on a hierarchical legal knowledge graph. In addition to the technical solutions of the above embodiments, it also has the following technical features.

[0067] Among them, the user feedback and improvement sub-module: collects user feedback on system functions, usage experience, etc., handles user problems and suggestions in a timely manner, and continuously optimizes system functions and interface design based on user feedback to improve user satisfaction.

[0068] When in use: by setting up the data acquisition unit, multimodal data middle platform module, data preprocessing module, quantum encryption security module, multimodal data fusion unit, multilingual intelligent processing module, dynamic optimization module, real-time update module, intelligent risk assessment module and user management module, the collection, evaluation, screening, encryption, storage and translation of data are realized, thereby realizing the powerful functions of this system, improving the collection and analysis of legal data, and being more practical.

[0069] The embodiments of the present application are described above in conjunction with the accompanying drawings. Unless there is a conflict, the embodiments and features in the embodiments of the present application can be combined with each other. The present application is not limited to the above-mentioned specific implementation methods. The above-mentioned specific implementation methods are merely illustrative and not restrictive. Under the guidance of this application, ordinary technicians in this field can also make many forms without departing from the purpose of this application and the scope of protection of the claims, all of which are within the protection of this application.

Claims

1. Intelligent legal affairs dynamic collaboration system based on hierarchical legal knowledge graph, characterized by ,include: The data collection unit supports the collection of various types of legal data, including but not limited to contract documents, emails, voice calls, video conference records, legal imaging materials, etc., and uses CR and ASR technologies to achieve structured conversion of unstructured data; A multimodal data middleware module, including a heterogeneous data fusion engine and a blockchain data safe, is used to achieve intelligent collection, semantic conversion, and secure sharing of multi-source legal data; The data preprocessing module performs cleaning operations such as deduplication, error correction, and format conversion on the collected data. It also fills missing values and processes outliers to ensure data accuracy and consistency. It performs preprocessing operations such as format unification and missing value filling to improve data quality. It uses natural language processing technology to preprocess text data through word segmentation, part-of-speech tagging, named entity recognition, etc. to extract key information. Quantum encryption security module, used to implement quantum encryption transmission and storage of legal data to ensure data security; The multimodal data fusion unit uses deep learning and other technologies to fuse different types of data, build a unified data representation, and explore the potential connections and value between data; The multilingual intelligent processing module, consisting of a legal terminology translation library, an optimized neural machine translation model, and a multilingual semantic parsing unit, enables accurate translation and in-depth analysis of multilingual legal documents; The dynamic optimization module is equipped with an environmental perception and data acquisition unit, a reinforcement learning agent, and an optimization decision execution unit, which can dynamically optimize the system process based on real-time environmental information; Real-time update module, including legal knowledge source monitoring unit, knowledge extraction and integration unit, knowledge push and application unit, to ensure that the system obtains and applies the latest legal knowledge in a timely manner; Dynamic optimization module, through the reinforcement learning agent of the dynamic optimization module through continuous trial and error and learning, optimizes the strategy according to environmental feedback, and realizes autonomous dynamic adjustment of system processes; The intelligent risk assessment module includes a legal knowledge graph construction submodule, a risk assessment submodule, and an intelligent retrieval and recommendation submodule, which is used to provide legal knowledge management, risk assessment, and intelligent decision-making assistance; The user management module includes a user authentication and authorization sub-module, a user behavior analysis sub-module, and a user feedback and improvement sub-module.

2. The intelligent legal affairs dynamic collaboration system based on hierarchical legal knowledge graph according to claim 1 is characterized in that: The quantum encryption security module includes a quantum key distribution unit, a data encryption and decryption unit, and a security authentication and access control unit. The quantum encryption security module uses the principle of quantum entanglement to distribute quantum keys and uses a quantum encryption algorithm to encrypt data.

3. The intelligent legal affairs dynamic collaboration system based on hierarchical legal knowledge graph according to claim 1 is characterized in that: The multimodal data processing module adopts OCR optical character recognition technology, ASR speech recognition technology and deep learning algorithm to realize the collection and integration of structured, semi-structured and unstructured data.

4. The intelligent legal affairs dynamic collaboration system based on hierarchical legal knowledge graph according to claim 1 is characterized in that: The real-time update module can monitor multiple legal knowledge sources in real time, automatically extract and integrate new knowledge, and push and apply it according to user needs and business scenarios. The real-time update module can monitor that the country where the case is located has newly promulgated a legal provision related to commercial disputes. The knowledge extraction and integration unit quickly extracts key content and integrates it into the system knowledge system. The knowledge push and application unit pushes the legal provision to all personnel involved in case handling, and automatically applies new knowledge in case analysis, litigation document writing and other links to ensure that case handling complies with the latest legal regulations.

5. The intelligent legal affairs dynamic collaboration system based on hierarchical legal knowledge graph according to claim 1 is characterized in that: The legal knowledge graph construction submodule of the intelligent risk assessment module integrates laws and regulations, judicial interpretations, judicial cases and academic literature to construct a legal knowledge graph containing legal concepts, legal relations and legal rules.

6. The intelligent legal affairs dynamic collaboration system based on hierarchical legal knowledge graph according to claim 1 is characterized in that: As stated.

7. The intelligent legal affairs dynamic collaboration system based on hierarchical legal knowledge graph according to claim 1 is characterized in that: The user authentication and authorization submodule adopts a multi-factor authentication method to ensure the authenticity and legitimacy of the user's identity, and allocates different operation permissions according to user roles and business needs to achieve fine-grained permission control.

8. The intelligent legal affairs dynamic collaboration system based on hierarchical legal knowledge graph according to claim 1 is characterized in that: The user behavior analysis submodule records the user's operating behavior in the system, uses big data analysis technology to mine and analyze user behavior, builds user portraits, understands user needs and preferences, and provides users with personalized services and recommendations.

9. The intelligent legal affairs dynamic collaboration system based on hierarchical legal knowledge graph according to claim 1 is characterized in that: The user feedback and improvement sub-module collects user feedback on system functions, user experience, etc., handles user issues and suggestions in a timely manner, and continuously optimizes system functions and interface design based on user feedback to improve user satisfaction.

Images