Automatic document generation method based on intelligent law enforcement

Abstract

The invention provides an automatic document generation method based on intelligent law enforcement. The method comprises the following steps: S1, constructing a law enforcement knowledge base; a law enforcement related knowledge base is formed based on laws and regulations, case types, case data, law enforcement processes and the like. S2, extracting key information; law enforcement and case handling key processes and key document information are advanced based on the knowledge base. S3, intelligently generating a document; and preliminarily generating document information based on the key information. S4, performing continuous optimization; and based on the preliminary document, a manager performs fine adjustment to form a system document template. According to the automatic document generation method based on intelligent law enforcement, the efficiency is effectively improved, the case handling time of law enforcement officers can be shortened through automatic processing, employees can more concentrate on important tasks, basic data are brought in through a system, and the possibility of human errors can be effectively reduced. And the document template can be timely and easily adjusted without the participation of research and development personnel.

Description

Technical Field

[0001] The present invention relates to the field of computer technology, and in particular to an automated document generation method based on intelligent law enforcement. Background Art

[0002] Urban management refers to the control behavior of the city's operation and development. It includes the city government's management of the city's public welfare, public facilities and public utilities, as well as the management of all urban activities, including economic, social and municipal management. In the process of urban management and administrative law enforcement, it is necessary to find the required documents from the law enforcement standard documents and fill in the relevant content before the circulation approval can be carried out.

[0003] The traditional method is usually for law enforcement officers to patrol and report incidents. Based on the specific type of case and relevant experience and knowledge, they will find out the laws and regulations that have been violated. They will then find the required documents from a series of standard law enforcement documents published by the Housing and Urban-Rural Development Bureau, fill in the relevant content, and then the documents will be circulated with the approval of the law enforcement process. This requires a high level of experience from the law enforcement officers, who need to know clearly which documents will be used in the case. It is also time-consuming, labor-intensive, and prone to errors. Summary of the invention

[0004] In view of the shortcomings of the prior art, the purpose of the present invention is to provide an automated document generation method based on intelligent law enforcement to solve the problems raised in the above-mentioned background technology. The present invention improves efficiency and accuracy and enhances scalability.

[0005] In order to achieve the above object, the present invention is implemented through the following technical solution: an automated document generation method based on intelligent law enforcement, comprising the following steps:

[0006] Step 1: Build a law enforcement knowledge base, which includes laws and regulations, case types and templates, and a case library;

[0007] Step 2: Extract key information, including natural language processing and knowledge graph;

[0008] Step 3: Intelligently generate law enforcement documents. The generation process includes case information input, analysis of applicable laws and regulations, document template selection, content filling and adjustment, preliminary generation and review;

[0009] Step 4: Continuous optimization, including feedback mechanism, knowledge base update, model training and optimization.

[0010] Furthermore, in step one, the process of collecting laws and regulations requires collecting and organizing all relevant laws and regulations, judicial interpretations, administrative rules, etc. to ensure the comprehensiveness and accuracy of the knowledge base.

[0011] Furthermore, in the process of constructing the case types and templates, corresponding law enforcement document templates are designed and organized according to common case types and law enforcement processes. These templates should cover the basic elements and format requirements of different case types.

[0012] Furthermore, in the process of establishing the case library, historical law enforcement cases are collected and organized, especially cases that are similar or related to the current case, so as to provide reference for the automatic generation of documents.

[0013] Furthermore, in the step 2, NLP technology is used to parse the case description and extract key information, such as party information, case facts, and dispute focus; a legal knowledge graph is constructed to represent laws and regulations, case types, law enforcement processes, etc. in the form of a graph structure for rapid retrieval and reasoning.

[0014] Furthermore, in the step three, when the case information is input, the specific circumstances of the case are input into the intelligent system, including the party information, case facts, evidence materials, etc.; in the legal and regulatory applicability analysis process, the system automatically retrieves relevant laws and regulations and case libraries based on the input case information to conduct legal applicability analysis.

[0015] Furthermore, the selection of document templates needs to be based on the case type and legal applicability analysis results, and the system selects the corresponding law enforcement document template; the system automatically fills in the key content in the document template based on the case information and legal provisions, and makes necessary adjustments and optimizations; after the system generates preliminary law enforcement documents, they will be reviewed and modified by law enforcement personnel to ensure the accuracy and legality of the documents.

[0016] Furthermore, the feedback mechanism in step four includes: collecting opinions and suggestions from law enforcement personnel during use, and continuously optimizing and improving the performance and functions of the intelligent system.

[0017] Furthermore, the law enforcement knowledge base will be regularly updated with newly enacted laws and regulations, judicial interpretations and administrative rules, etc., to ensure that the system can keep pace with legal developments.

[0018] Furthermore, based on new case data and user feedback, the machine learning model or AI big model is continuously optimized and adjusted to improve the accuracy and efficiency of generated documents.

[0019] Beneficial effects of the present invention:

[0020] 1. This automated document generation method based on smart law enforcement effectively improves efficiency. Through automated processing, it can shorten the processing time of law enforcement personnel in handling cases, allowing employees to focus more on important tasks.

[0021] 2. This automated document generation method based on smart law enforcement improves accuracy and can effectively reduce the possibility of human error by introducing basic data into the system.

[0022] 3. This automated document generation method based on smart law enforcement has enhanced scalability and can adjust document templates in a timely and easy manner without the involvement of R&D personnel. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] Figure 1 This is a flow chart of an automated document generation method based on intelligent law enforcement according to the present invention. DETAILED DESCRIPTION

[0024] In order to make the technical means, creative features, objectives and effects achieved by the present invention easy to understand, the present invention is further explained below in conjunction with specific implementation methods.

[0025] See also Figure 1 The present invention provides the following technical solutions: an automated document generation method based on intelligent law enforcement, the method comprising: data collection and preprocessing, the system first collects law enforcement-related data through various channels, including case information, laws and regulations, law enforcement procedures, etc., and performs preprocessing and standardization processing; intelligent analysis and reasoning, using artificial intelligence algorithms to perform intelligent analysis and reasoning on the preprocessed data, and automatically generates preliminary content of law enforcement documents according to the specific circumstances of the case and the requirements of relevant laws and regulations; manual review and correction, the system presents the generated preliminary content to law enforcement personnel for manual review and correction to ensure the accuracy and legality of the document; electronic signature and authentication, after the review is passed, the system provides electronic signature and authentication services for law enforcement documents to ensure the authenticity and non-tamperability of the documents; output and sharing, the system outputs the generated law enforcement documents in electronic form and stores them in the server for subsequent query and sharing.

[0026] This embodiment also provides the following specific process:

[0027] S1, build a law enforcement knowledge base; form a law enforcement related knowledge base based on laws and regulations, case types, case data, law enforcement procedures, etc.

[0028] S2, extract key information; based on the knowledge base, obtain key law enforcement process and key document information in advance.

[0029] S3, intelligent document generation; based on key information, preliminary document information is generated.

[0030] S4, continuous optimization; based on the preliminary documents, managers make minor adjustments to form a system document template, including:

[0031] (1) Building a law enforcement knowledge base

[0032] 1. Collect laws and regulations: First, you need to collect and organize all relevant laws and regulations, judicial interpretations, administrative rules, etc. to ensure the comprehensiveness and accuracy of the knowledge base.

[0033] 2. Organize case types and templates: Design and organize corresponding law enforcement document templates based on common case types and law enforcement processes. These templates should cover the basic elements and format requirements of different case types.

[0034] 3. Establish a case library: Collect and organize historical law enforcement cases, especially those that are similar or related to the current case, to provide reference for the automatic generation of documents.

[0035] (2) Extracting key information

[0036] 1. Natural Language Processing: Use NLP technology to parse case descriptions and extract key information, such as party information, case facts, and dispute focus.

[0037] 2. Knowledge graph: Build a legal knowledge graph to represent laws and regulations, case types, law enforcement processes, etc. in the form of a graph structure for quick retrieval and reasoning.

[0038] (3) Intelligent generation of law enforcement documents

[0039] 1. Case information input: Input the specific circumstances of the case into the intelligent system, including information about the parties involved, case facts, and evidence materials.

[0040] 2. Analysis of the applicability of laws and regulations: Based on the input case information, the system automatically retrieves relevant laws and regulations and case libraries to conduct legal applicability analysis.

[0041] 3. Document template selection: Based on the case type and legal applicability analysis results, the system selects the corresponding law enforcement document template.

[0042] 4. Content filling and adjustment: The system automatically fills in the key content in the document template based on the case information and legal terms, and makes necessary adjustments and optimizations.

[0043] 5. Preliminary generation and review: After the system generates the preliminary law enforcement documents, they will be reviewed and modified by law enforcement personnel to ensure the accuracy and legality of the documents.

[0044] (4) Continuous Optimization

[0045] 1. Feedback mechanism: Collect opinions and suggestions from law enforcement personnel during use, and continuously optimize and improve the performance and functions of the intelligent system.

[0046] 2. Knowledge base update: Regularly update the law enforcement knowledge base, including newly enacted laws and regulations, judicial interpretations and administrative rules, to ensure that the system can keep pace with legal developments.

[0047] 3. Model training and optimization: Based on new case data and user feedback, continuously optimize and adjust machine learning models or AI big models to improve the accuracy and efficiency of generated documents.

[0048] The basic principles and main features of the present invention and the advantages of the present invention are shown and described above. For those skilled in the art, it is obvious that the present invention is not limited to the details of the above exemplary embodiments, and the present invention can be implemented in other specific forms without departing from the spirit or basic characteristics of the present invention.

[0049] In addition, it should be understood that although the present specification is described according to implementation modes, not every implementation mode contains only one independent technical solution. This description of the specification is only for the sake of clarity. Those skilled in the art should regard the specification as a whole. The technical solutions in each embodiment may also be appropriately combined to form other implementation modes that can be understood by those skilled in the art.

Claims

1. An automated document generation method based on intelligent law enforcement, characterized in that: The following steps are involved: Step 1: Build a law enforcement knowledge base, which includes laws and regulations, case types and templates, and a case library; Step 2: Extract key information, including natural language processing and knowledge graph; Step 3: Intelligently generate law enforcement documents. The generation process includes case information input, analysis of applicable laws and regulations, document template selection, content filling and adjustment, preliminary generation and review; Step 4: Continuous optimization, including feedback mechanism, knowledge base update, model training and optimization.

2. The method for generating automated documents based on intelligent law enforcement according to claim 1, characterized in that: In step one, the process of collecting laws and regulations requires collecting and organizing all relevant laws and regulations, judicial interpretations, administrative rules, etc. to ensure the comprehensiveness and accuracy of the knowledge base.

3. The method for generating automated documents based on intelligent law enforcement according to claim 2, characterized in that: In the process of constructing the case types and templates, corresponding law enforcement document templates are designed and organized according to common case types and law enforcement procedures, and the templates should cover the basic elements and format requirements of different case types.

4. The method for generating automated documents based on intelligent law enforcement according to claim 3 is characterized in that: In the process of establishing the case library, historical law enforcement cases are collected and organized, especially cases that are similar or related to the current case, so as to provide reference for the automatic generation of documents.

5. The method for generating automated documents based on intelligent law enforcement according to claim 1 is characterized in that: In the step 2, NLP technology is used to parse the case description and extract key information, such as party information, case facts, and dispute focus; a legal knowledge graph is constructed to represent laws and regulations, case types, law enforcement processes, etc. in the form of a graph structure for rapid retrieval and reasoning.

6. The method for generating automated documents based on intelligent law enforcement according to claim 1, characterized in that: In the step three, when case information is input, the specific circumstances of the case are input into the intelligent system, including party information, case facts, evidence materials, etc.; in the legal and regulatory applicability analysis process, the system automatically retrieves relevant laws and regulations and case libraries based on the input case information to conduct legal applicability analysis.

7. The method for generating automated documents based on intelligent law enforcement according to claim 6, characterized in that: The selection of document templates needs to be based on the case type and the results of the applicable law analysis. The system selects the corresponding law enforcement document template; The system automatically fills in the key content in the document template based on the case information and legal provisions, and makes necessary adjustments and optimizations; after the system generates the preliminary law enforcement document, it will be reviewed and modified by law enforcement personnel to ensure the accuracy and legality of the document.

8. The method for generating automated documents based on intelligent law enforcement according to claim 1, characterized in that: The feedback mechanism in step 4 includes: collecting opinions and suggestions from law enforcement personnel during use, and continuously optimizing and improving the performance and functions of the intelligent system.

9. The method for generating automated documents based on intelligent law enforcement according to claim 8, characterized in that: The law enforcement knowledge base is updated regularly, including newly enacted laws and regulations, judicial interpretations, and administrative rules, to ensure that the system can keep pace with legal developments.

10. The method for generating automated documents based on intelligent law enforcement according to claim 9, characterized in that: Based on new case data and user feedback, we continuously optimize and adjust machine learning models or AI big models to improve the accuracy and efficiency of generated documents.

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