Java development-based court electronic filing material arrangement system
By designing a court electronic archive material sorting system developed based on Java, using technologies such as automatic classification, intelligent retrieval and multi-format integration, the problems of low efficiency, error prone and lack of intelligent processing capabilities in the existing technology are solved, and the problem of low efficiency, error prone and lack of intelligent processing capabilities is realized. Efficient, accurate and safe electronic material management.
Patent Information
- Application Number
- CN202411556195.8
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2024-11-04
- Publication Date
- 2025-02-14
AI Technical Summary
The existing technology has problems such as inefficient, error-prone and lack of intelligent processing capabilities in the collation of electronic archived materials in courts, and it is difficult to adapt to the needs of complex cases and large-scale data management.
Design a court electronic archive material sorting system developed based on Java, including automatic classification module, intelligent search module and material integration module. It adopts natural language processing, image recognition, full-text search and semantic search technology to support multi-format file integration and through Permission management and data encryption modules ensure system security.
It significantly improves the efficiency of electronic materials sorting and search, reduces manual operation time and errors, ensures the accuracy and completeness of materials, simplifies the material management process, and ensures data security.
Smart Images
Figure CN119441460A_ABST
Abstract
Description
Technical Field
[0001] The present invention relates to the technical field of judicial informatization, and in particular to a Java-based solution for solving the problem of court electronic filing material sorting system. Background Art
[0002] In today's digital age, courts still mainly handle electronic archived materials through manual sorting or simple file management systems. However, these traditional methods have significant limitations. First, although manual sorting is intuitive, its inefficient operation not only increases the burden on staff, but also easily leads to errors. With the increase in the number of cases and the increasing complexity of electronic materials, the limitations of manual sorting have become increasingly prominent. Manual operations are prone to problems such as duplication of work, inaccurate classification, and file loss, which not only affects work efficiency, but may also lead to the omission or mis-filing of important information, which in turn has a negative impact on the handling of cases and trial results. Secondly, existing file management systems, which are usually based on traditional folder structures, can provide basic storage and retrieval functions, but are unable to cope with the growing number of electronic materials. These systems often lack flexibility and scalability and cannot adapt to the ever-changing case management needs. Especially in complex cases or cross-departmental collaboration, traditional file systems are difficult to support efficient document circulation and real-time multi-party collaborative processing. In addition, such systems lack intelligent processing capabilities and cannot automatically classify, analyze content, or intelligently retrieve materials, resulting in users spending time and effort to find information in massive data. For the management and analysis of large-scale data, the performance of these systems may also become a bottleneck, affecting the overall workflow.
[0003] Therefore, it is necessary to design a Java-based solution to the court electronic archiving material organization system that is efficient, easy to use, and not prone to errors, and can greatly improve the work efficiency of the court. Summary of the invention
[0004] 1. Technical issues to be resolved
[0005] In view of the deficiencies in the prior art, the present invention provides a Java-based solution to the court electronic archiving material organization system, which has the advantages of being efficient, easy to use, and not prone to errors, and can greatly improve the work efficiency of the court, solving the problems in the above-mentioned background technology.
[0006] (II) Technical solution
[0007] In order to achieve the above-mentioned purpose of being efficient, easy to use, not prone to errors, and being able to greatly improve the work efficiency of the court, the present invention provides the following technical solutions: a Java-based solution to the court electronic archiving material organization system, including a core function module and a permission management module, the core function module including an automatic classification module, an intelligent retrieval module and a material integration module, the automatic classification module including document classification based on keywords and content, the keyword-based document classification including the application of natural language processing technology in document classification, the content-based document classification including the application of image recognition technology in document classification and the application of document structure analysis in classification, the intelligent retrieval module including full-text retrieval technology and semantic retrieval technology, the full-text retrieval technology including the construction and optimization of inverted indexes and keyword weight calculation and sorting, the semantic retrieval technology including ontology-based semantic retrieval and deep learning-based semantic matching, the material integration module including document merging and splitting and document version management, the document merging and splitting including document merging rules and strategies and document splitting scenarios and methods, the document version management including version control mechanism and version difference comparison and merging.
[0008] Preferably, the authority management module includes a user authentication module and a data encryption module, the user authentication module includes user registration and login and user authority allocation, the user registration and login include user information verification and login session management, the user authority allocation includes role and authority mapping and dynamic adjustment of authority, the data encryption module includes data encryption algorithm and data decryption and verification, the data encryption algorithm includes symmetric encryption algorithm and asymmetric encryption algorithm, and the data decryption and verification includes decryption key management and data integrity verification.
[0009] Preferably, the natural classification module adopts a text classification algorithm in natural language processing technology, such as TF-IDF combined with a naive Bayes classifier or a support vector machine algorithm, to perform content analysis and classification on electronic materials. Through a pre-trained classification model, the system can automatically identify the subject of the material and classify it into corresponding categories.
[0010] The above technical solution is used to further divide the text data into a collection of words or phrases, filter out common words that do not affect the text topic, restore the words to their root form, and measure the relative importance of each word to the text by calculating the word frequency and inverse document frequency. TF-IDF can effectively reduce the impact of common words while highlighting important words. Based on Bayes' theorem and the independence assumption of features, the model is suitable for processing text data with high dimensions. Linear or nonlinear decision boundaries are used to classify data points into different categories. SVM is suitable for processing complex classification tasks. The model is trained using annotated training data sets, and the hyperparameters of the model are adjusted using cross-validation technology to improve the accuracy and generalization ability of classification. The trained model is deployed to the system to process new electronic materials. When new text data is input, the system automatically applies the classifier to analyze and classify the text. The system outputs the classification results and classifies the electronic materials into predefined categories, such as legal documents, technical manuals, user guides, etc. The system regularly updates the training data set and retrains the model to adapt to new content and changes in classification requirements to ensure continuous improvement in classification accuracy.
[0011] Preferably, the intelligent search module uses a full-text search engine such as Apache Lucene or Elasticsearch to achieve fast and accurate material retrieval. The implementation logic of the full-text search technology is as follows:
[0012] When materials are uploaded, the system first performs word segmentation on the content, dividing the text into independent words or phrases, and then removes stop words that do not contribute to text analysis, such as common conjunctions and prepositions, to clean the text data. Subsequently, the system creates an inverted index for the processed text, associating each word with the location of the document in which it resides. This process ensures that in subsequent classification and retrieval, the system can quickly locate and analyze the content of the material, achieving efficient and accurate document management.
[0013] When the user enters the search keyword, the system first performs the same preprocessing steps on the keyword as when uploading the material, including word segmentation and removal of stop words. The preprocessed keywords will be used to find matching documents in the inverted index. The system quickly locates the location of documents containing these keywords and returns a list of related documents, thereby achieving accurate and efficient search results.
[0014] According to the relevance algorithm, the matching results are sorted and returned to the user. The formula is as follows:
[0015]
[0016] Where D is the vector representation of the document, Q is the vector representation of the query, t is each word that appears in the query and the document, TF-IDF(t,D) is the TF-IDF value of word t in document D, and TF-IDF(t,Q) is the TF-IDF value of word t in query Q;
[0017] The frequency of word t appearing in document D is as follows:
[0018]
[0019] The prevalence of word t in all documents is as follows:
[0020]
[0021] The final relevance score, the higher the score, the stronger the relevance of document D to query Q.
[0022] Preferably, the material integration module supports automatic integration of multiple file formats, such as PDF, Word, and Excel. The system converts files of different formats into a unified PDF format through a file conversion tool and merges them according to a preset template.
[0023] The system that adopts the above technical solution will further use file conversion tools to convert files of different formats into a unified PDF format. After the conversion is completed, the system will merge these PDF files in a specific order and layout according to the preset template to generate a unified PDF document. The preset template can include elements such as page numbering, title page, and table of contents page to ensure that the structure of the merged document is clear and consistent. This process realizes the seamless integration of different file formats, which is convenient for archiving and sharing.
[0024] Preferably, the permission management module adopts a role-based access control model, and users with different roles have different access rights. The permission management logic is as follows:
[0025] User authentication: When a user logs in, the system authenticates the user through the user name and password and obtains the user's role information;
[0026] Permission allocation: Based on the user role, the system allocates corresponding permissions to the user;
[0027] Access control: When users access system resources, the system performs access control based on their roles and permissions.
[0028] Preferably, the data encryption module uses data encryption technology to encrypt sensitive data during storage and transmission.
[0029] (III) Beneficial effects
[0030] Compared with the prior art, the present invention provides a Java-based solution to the court electronic filing material sorting system, which has the following beneficial effects:
[0031] The present invention significantly improves the efficiency of electronic material organization and search through automatic classification and intelligent retrieval functions, and reduces manual operation time; reduces errors in manual operation through systematic automatic processing, and ensures the accuracy and completeness of materials; simplifies the material management process through multi-format integration functions, making it convenient for users to view and use electronic materials; and ensures the security and confidentiality of materials through the authority management system to prevent unauthorized access and modification. BRIEF DESCRIPTION OF THE DRAWINGS
[0032] Figure 1 It is a schematic diagram of the process of the present invention;
[0033] Figure 2 It is a schematic diagram of the structure of the present invention;
[0034] Figure 3 It is a schematic diagram of an example of the present invention. DETAILED DESCRIPTION
[0035] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.
[0036] Example 1
[0037] The present invention provides a technical solution: a Java-based solution for a court electronic archiving material organization system, comprising a core function module and a permission management module, wherein the core function module comprises an automatic classification module, an intelligent retrieval module and a material integration module, wherein the automatic classification module comprises document classification based on keywords and content, wherein the keyword-based document classification comprises the application of natural language processing technology in document classification, wherein the content-based document classification comprises the application of image recognition technology in document classification and the application of document structure analysis in classification, wherein the intelligent retrieval module comprises full-text retrieval technology and semantic retrieval technology, wherein the full-text retrieval technology comprises the construction and optimization of inverted indexes and the calculation and sorting of keyword weights, wherein the semantic retrieval technology comprises ontology-based semantic retrieval and deep learning-based semantic matching, wherein the material integration module comprises document merging and splitting and document version management, wherein the document merging and splitting comprises the rules and strategies for document merging and the scenarios and methods for document splitting, and wherein the document version management comprises the version control mechanism and the comparison and merging of version differences.
[0038] The authority management module includes a user authentication module and a data encryption module. The user authentication module includes user registration and login and user authority allocation. The user registration and login include user information verification and login session management. The user authority allocation includes mapping of roles and authorities and dynamic adjustment of authorities. The data encryption module includes data encryption algorithm and data decryption and verification. The data encryption algorithm includes symmetric encryption algorithm and asymmetric encryption algorithm. The data decryption and verification includes decryption key management and data integrity verification.
[0039] The permission management module adopts a role-based access control model. Users with different roles have different access rights. The permission management logic is as follows:
[0040] (1) When a user logs in, the system first receives the user name and password entered by the user and verifies them against the credentials stored in the database. After identity authentication, the system queries the user's role information based on the user name. This role information is usually stored in a database table related to the user account, which defines the user's permissions and accessible resources in the system. After the system obtains the role information, it sets the appropriate permission level based on the role, allowing the user to access specific functional modules and data. The system can ensure that users operate within their permissions to ensure security and functional effectiveness.
[0041] (2) The system administrator predefines different roles, each of which corresponds to a different set of permissions. These roles may include administrator, editor, viewer, etc. Each role has specific operation permissions, such as read, write, modify, delete, etc. After the user successfully logs in and authenticates, the system queries the user's role information based on the user name or user ID. This information is usually stored in a database, associating users with their roles. The system loads the permission set associated with the user's role based on the user's role. These permissions define the modules, functions, and data ranges that the user can access. For example, the administrator role may have full system permissions, while ordinary users may only be limited to viewing and editing their own data. When the user operates, the system checks in real time whether the operation is within the user's permission range. If the user attempts to perform an operation beyond his or her permission, the system will reject the request and give a prompt message to prevent unauthorized access and operation.
[0042] (3) When a user requests access to a resource, such as viewing specific data, performing an operation, or entering a module, the system will first intercept the request and identify the user's identity and role information; based on the user's role information, the system will query the pre-defined permission list to determine whether the user has permission to access the resource. Permissions are usually implemented in the form of an access control list (ACL) or a role-based access control (RBAC) model; the system will match the requested resource with the resources in the permission list. For example, a data table, operation button, or folder may only be open to users with an administrator role, while ordinary users may not have access to it; if the user has the corresponding access rights, the system will allow the request to pass, and the user can access the resource or perform the operation normally. If the user does not have access rights, the system will reject the request and usually return an error message or redirect to a page indicating that the user does not have permission.
[0043] The data encryption module uses data encryption technology to encrypt sensitive data in storage and transmission. The system uses a symmetric encryption algorithm when storing data. The AES algorithm encrypts data through a symmetric key, converts plaintext data into ciphertext and stores it in the database or file system. During data transmission, the system uses TLS / SSL protocols, which provide an encrypted channel for data transmission to ensure that data transmitted on the network will not be stolen or tampered with; the system generates and manages keys for encryption and decryption operations, and the keys are usually stored in a secure key management system, and access to the keys is strictly controlled to prevent unauthorized key use; when the system needs to save sensitive data, the data is first encrypted using the AES algorithm The system encrypts the data and then stores the generated ciphertext in the database or file system. When the data needs to be transmitted over the network, the system uses the TLS / SSL protocol to establish an encrypted connection and transmits the data through an encrypted channel to prevent man-in-the-middle attacks and data leakage. When it is necessary to read the stored sensitive data, the system retrieves the ciphertext from the database and decrypts it using the symmetric key used in the storage encryption process, restoring it to plaintext for use by the application. When receiving data transmitted through an encrypted channel, the system automatically decrypts the transmitted data packet to ensure that the received content is complete and secure. The system also uses hash functions to verify the integrity of the data during the encryption and decryption process to ensure that the data has not been tampered with during transmission or storage.
[0044] Example 2
[0045] CourtArchivingSystem: The core class of the system, which contains instances of all modules and provides methods for processing materials, retrieving materials, integrating materials, managing permissions, data encryption and user authentication.
[0046] ClassificationModule: Responsible for the automatic classification of materials, using the NLP engine to analyze and classify the material content.
[0047] SearchModule: Provides full-text search capabilities, using search engines to index and retrieve materials.
[0048] IntegrationModule: handles the integration of multi-format files, converts files of different formats into a unified format and integrates them.
[0049] PermissionModule: Role-based permission management, assigning user roles and checking permissions.
[0050] EncryptionModule: Provides data encryption and decryption functions to ensure data security.
[0051] AuthenticationModule: Responsible for user authentication, verifying username and password, and returning user information.
[0052] NLPEngine, SearchEngine, FileConverter, EncryptionAlgorithm: used for the specific implementation of natural language processing, full-text retrieval, file conversion and data encryption respectively.
[0053] User, Role, Permission: The basic classes of users, roles, and permissions, which define the user role and permission management.
[0054] It should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including 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.
[0055] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.
Claims
1. A Java-based solution to the court electronic filing material sorting system, characterized by: It includes a core function module and a permission management module. The core function module includes an automatic classification module, an intelligent retrieval module and a material integration module. The automatic classification module includes document classification based on keywords and content. The keyword-based document classification includes the application of natural language processing technology in document classification. The content-based document classification includes the application of image recognition technology in document classification and the application of document structure analysis in classification. The intelligent retrieval module includes full-text retrieval technology and semantic retrieval technology. The full-text retrieval technology includes the construction and optimization of inverted indexes and keyword weight calculation and sorting. The semantic retrieval technology includes ontology-based semantic retrieval and deep learning-based semantic matching. The material integration module includes document merging and splitting and document version management. The document merging and splitting includes rules and strategies for document merging and scenarios and methods for document splitting. The document version management includes version control mechanism and version difference comparison and merging.
2. According to the Java-based solution to the court electronic filing material arrangement system of claim 1, it is characterized by: The authority management module includes a user authentication module and a data encryption module. The user authentication module includes user registration and login and user authority allocation. The user registration and login include user information verification and login session management. The user authority allocation includes mapping of roles and authorities and dynamic adjustment of authorities. The data encryption module includes a data encryption algorithm and data decryption and verification. The data encryption algorithm includes a symmetric encryption algorithm and an asymmetric encryption algorithm. The data decryption and verification includes decryption key management and data integrity verification.
3. According to the Java-based solution to the court electronic filing material arrangement system of claim 1, it is characterized in that: The natural classification module adopts text classification algorithms in natural language processing technology, such as TF-IDF combined with naive Bayes classifier or support vector machine algorithm, to perform content analysis and classification on electronic materials. Through the pre-trained classification model, the system can automatically identify the subject of the material and classify it into the corresponding category.
4. According to the Java-based solution to the court electronic filing material arrangement system of claim 1, it is characterized in that: The intelligent search module uses a full-text search engine such as Apache Lucene or Elasticsearch to achieve fast and accurate material retrieval. The implementation logic of the full-text search technology is as follows: When the material is uploaded, the system first performs word segmentation on the content, dividing the text into independent words or phrases, and then removes stop words that do not contribute to text analysis, such as common conjunctions and prepositions, to clean the text data. Subsequently, the system creates an inverted index for the processed text, associating each word with the position of the document in which it is located, so that the system can quickly locate and analyze the content of the material; When the user enters the search keyword, the system first performs the same preprocessing steps on the keyword as when the material is uploaded, including word segmentation and removal of stop words. The preprocessed keywords will be used to find matching documents in the inverted index. The system quickly locates the location of the document containing these keywords and returns a list of related documents. According to the relevance algorithm, the matching results are sorted and returned to the user. The formula is as follows: Where D is the vector representation of the document, Q is the vector representation of the query, t is each word that appears in the query and the document, TF-IDF(t,D) is the TF-IDF value of word t in document D, and TF-IDF(t,Q) is the TF-IDF value of word t in query Q; The frequency of word t appearing in document D is as follows: The prevalence of word t in all documents is as follows: The final relevance score, the higher the score, the stronger the relevance of document D to query Q.
5. According to the Java-based solution to the court electronic filing material arrangement system of claim 1, it is characterized in that: The material integration module supports automatic integration of multiple file formats, such as PDF, Word, and Excel. The system converts files of different formats into a unified PDF format through a file conversion tool and merges them according to a preset template.
6. According to the Java-based solution to the court electronic filing material arrangement system of claim 1, it is characterized in that: The permission management module adopts a role-based access control model. Users with different roles have different access rights. The permission management logic is as follows: User authentication: When a user logs in, the system authenticates the user through the user name and password and obtains the user's role information; Permission allocation: Based on the user role, the system allocates corresponding permissions to the user; Access control: When users access system resources, the system performs access control based on their roles and permissions.
7. According to the Java-based solution to the court electronic filing material arrangement system of claim 2, it is characterized in that: The data encryption module uses data encryption technology to encrypt sensitive data in storage and transmission.