AI-based legal resource scheduling method and system

Abstract

The invention relates to the technical field of legal resource retrieval, and discloses an AI-based legal resource scheduling method and system. User legal resource retrieval platform intelligent screening is carried out based on user occupational role type identification information and user legal resource demand type judgment information in combination with an AI intelligent algorithm and scientifically preset legal resource retrieval platform feature information, and meanwhile a legal resource retrieval platform screening result is visually output in time in combination with a display screen. A legal resource retrieval platform is customized and reliably matched based on user occupational characteristics and legal resource requirements, and visual and efficient output is carried out; based on the legal resource demand feature information of the user, a target legal resource retrieval platform screens information and timely constructs legal resource scheduling index information in combination with data processing science, meanwhile, accurate retrieval and acquisition of legal resource data needed by the user are achieved in combination with an internet search platform, and the response efficiency and satisfaction degree of legal resource scheduling are improved.

Description

Technical Field

[0001] This invention relates to the technical field of legal resource retrieval, specifically to an AI-based legal resource scheduling method and system. Background Technology

[0002] Laws and regulations form the foundation of legal resources, including normative documents with legal force such as the Constitution, laws, administrative regulations, and local regulations. These normative documents stipulate the rights and obligations of citizens, as well as the organization and powers of state organs, and serve as important bases for maintaining social order and fairness. With the development of information technology, legal databases and information systems have emerged as new forms of legal resources. These systems integrate various legal resources such as laws and regulations, legal cases, and legal documents, providing convenient retrieval, query, and analysis functions. However, existing legal resource retrieval processes cannot achieve customized matching of legal resource retrieval platforms based on user professional roles and types of user legal resource needs, nor can they accurately retrieve legal resource text information based on user legal resource needs, thus reducing the accuracy and satisfaction of legal resource retrieval.

[0003] Chinese invention patent application CN118503403A, published on August 16, 2024, discloses a method, system, device, and storage medium for recommending legal provisions in low-resource learning scenarios. The method involves inputting case fact text; converting the sentences of the input case fact text into word vectors using pre-trained word vectors and word segmentation algorithms; establishing a deep learning model capable of classifying a large number of legal provision tags; further encoding the converted word vectors using a recurrent neural network; calculating the relevance scores between legal provision tags to enhance the representation of corresponding tags; training using a binary cross-entropy loss function, with the model output layer providing the probability distribution for each category, and selecting the categories with the highest probabilities as the recommended legal provisions. This method effectively handles a large number of legal provision tags with limited training data, improving the accuracy and recall of multi-tag legal provision classification. However, the above technical solution cannot intelligently and accurately match legal resource information based on the user's professional role and legal resource needs. Summary of the Invention

[0004] (a) Technical problems to be solved To address the issues raised by existing legal resource retrieval processes, such as the inability to customize legal resource retrieval platforms based on user professional roles and types of legal resource needs, and the inability to accurately retrieve legal resource text information based on user legal resource needs, thus reducing the accuracy and satisfaction of legal resource retrieval, this paper aims to achieve the following objectives: accurate analysis of user professional roles, efficient analysis of user legal resource needs, customized matching of legal resource retrieval platforms, accurate retrieval of legal resource text information required by users, and improved accuracy and satisfaction of legal resource retrieval.

[0005] (II) Technical Solution This invention is achieved through the following technical solution: an AI-based legal resource scheduling method, the method comprising the following steps: S1. Collect user occupational characteristic information and user legal resource demand characteristic information, identify the user's occupational role type, and obtain user occupational role type identification information; process the user's legal resource demand type to obtain user legal resource demand type judgment information. S2. Based on the user's professional role type and legal resource needs type, filter out the legal resource search platforms required by the user, obtain the target legal resource search platform filtering information and output it; S3. Based on the user's legal resource needs information and the selected legal resource retrieval platform feature information, construct legal resource scheduling index information and execute legal resource scheduling operations to obtain real-time legal resource scheduling feedback information.

[0006] Preferably, the process of collecting user occupational characteristic information and user legal resource demand characteristic information to identify the user's occupational role type and obtain user occupational role type identification information; and judging the user's legal resource demand type to obtain user legal resource demand type judgment information includes the following steps: S11. Collect the text information describing the specific work characteristics of the user's occupation online through the data input dialog box, and obtain the user's occupational characteristic information; the user's occupational characteristic information includes occupational name characteristic information, occupational level characteristic information, occupational skill characteristic information, and work nature characteristic information; The system collects the textual information of legal resources required by the user online through a data input dialog box, and obtains the user's legal resource demand feature information. The user's legal resource demand feature information includes the specific type of legal resources required by the user and the specific scenario description of the legal event. S12. Based on the user's occupational characteristic information and the standard occupational characteristic information set of different user occupational roles, perform user occupational role type identification processing to obtain user occupational role type identification information. S13. Based on the user's legal resource demand characteristic information and the user's different legal resource standard characteristic information set, perform user legal resource demand type judgment processing to obtain user legal resource demand type judgment information.

[0007] Preferably, the process of identifying user occupational role types based on the user's occupational characteristic information and the standard occupational characteristic information set for different user occupational roles, to obtain user occupational role type identification information, includes the following steps: S121. Construct a standard occupational characteristic information set for different user occupational roles. ,in Indicates the first The document contains standard occupational characteristic information for different user occupational roles, including lawyers, corporate legal counsel, accountants, teachers, and mechanical engineers. The standard occupational characteristic information for different user occupational roles refers to standard occupational characteristic text information set for different user occupational role types. S122. Using the Word2Vec text search algorithm, the user's occupational characteristic information is compared with the standard occupational characteristic information set of different user occupational roles. Standard occupational characteristic information for different user occupational roles described in the document Perform occupational characteristic text information matching to search for standard occupational characteristic information of different user occupational roles that match the user's occupational characteristic information. The corresponding user job role type text information is obtained, and user job role type identification information is obtained.

[0008] Preferably, the process of determining the type of user's legal resource needs based on the user's legal resource needs characteristic information and the user's different legal resource standard characteristic information sets, to obtain the user's legal resource needs type determination information, includes the following steps: S131. Construct a set of standard feature information of different legal resources for users. ,in Indicates the first The user's different legal resource standard feature information corresponding to different types of legal resources, where legal resource types include laws and regulations, legal cases, and legal documents; the user's different legal resource standard feature information represents the standard legal resource feature text information set for different types of legal resources. S132. Using the GloVe text search algorithm, the user's legal resource demand feature information is compared with the user's different legal resource standard feature information set. The different legal resource standard feature information of users described in the article Perform legal resource feature character analysis to search for different legal resource standard feature information of the user that matches the user's legal resource demand feature information. The corresponding legal resource type text information is obtained, and the user's legal resource requirement type judgment information is obtained.

[0009] Preferably, based on the user's professional role type and legal resource needs type, the user's required legal resource search platforms are selected, and the target legal resource search platform selection information is obtained and output, including the following steps: S21. Based on the user's professional role type identification information, the user's legal resource demand type judgment information, and the legal resource retrieval platform feature information matrix, perform the filtering process for the legal resource retrieval platform required by the user to obtain the target legal resource retrieval platform filtering information. S22. Output the generated target legal resource retrieval platform filtering information through the display screen and perform the legal resource retrieval platform filtering result output operation.

[0010] Preferably, the process of filtering the legal resource retrieval platforms required by the user based on the user's professional role type identification information, the user's legal resource need type judgment information, and the feature information matrix of the legal resource retrieval platform, to obtain the target legal resource retrieval platform filtering information, includes the following steps: S211. Constructing a feature information matrix for a legal resource retrieval platform. ,in Indicates the first The document describes the characteristic information of legal resource retrieval platforms corresponding to different types of legal resource demand scenarios. The legal resource demand scenario type is represented by an index data type formed by combining user professional role type information and legal resource demand type information to filter legal resource retrieval platforms. The legal resource retrieval platform characteristic information represents the characteristic text information of the optimal legal resource retrieval platform set for different legal resource demand scenario types. The legal resource retrieval platform characteristic information includes name, website, establishment time information, and a brief description of data resource content. The legal resource retrieval platforms include Peking University Law Database, Weike Xianxing, Faxin, and LexisNexis. S212. Combine the user's professional role type identification information, the user's legal resource demand type judgment information, and the feature information matrix of the legal resource retrieval platform. Feature information of the legal resource retrieval platform described in the article By performing keyword matching between user professional role type and legal resource type, the feature information of the legal resource retrieval platform corresponding to the user professional role type identification information and the user legal resource demand type judgment information is retrieved. The specific steps for constructing the target legal resource retrieval platform's filtering information are as follows: S2121, Initialization phase, in the feature information matrix of the legal resource retrieval platform The search space of the legal resource platform is updated with the whale population location and the maximum iteration algorithm T. The formula for updating the whale population location in the legal resource platform search is as follows: ,in This indicates a search for individual whales on a legal resource platform. The feature information matrix of the legal resource retrieval platform The location in the search space, and These represent the feature information matrix of individual whales searched on the legal resource platform. The upper and lower bounds in the search space, Indicates the value Random numbers within the interval; S2122, Encirclement of Prey Stage: The legal resource platform searches for individual whales within the feature information matrix of the legal resource retrieval platform. Search the search space for legal resource retrieval platform feature information that matches the user's professional role type identification information and the user's legal resource need type judgment information. When hunting, the system will select the legal resource retrieval platform feature information that best matches the user's professional role type identification information and the user's legal resource need type judgment information. The search engine on the legal resource platform locates individual whales swimming or randomly selects legal resource retrieval platform feature information that matches the user's professional role type identification information and the user's legal resource need type judgment information. Search for individual whales swimming on legal resource platforms based on their location; S21221, When selecting the feature information of the legal resource retrieval platform that best matches the user's professional role type identification information and the user's legal resource demand type judgment information. When searching for the location of an individual whale on a legal resource platform, the formula for updating the location of that whale is as follows: ;in This indicates that after the (t+1)th iteration, the legal resource platform searches for individual whales. The feature information matrix of the legal resource retrieval platform The location in the search space, This indicates that after the t-th iteration, the legal resource platform searches for individual whales. The feature information matrix of the legal resource retrieval platform The location in the search space, This represents the feature information matrix of the search whale individual on the legal resource platform after the t-th iteration. The optimal position in the search space. Indicates the value Random numbers within, The initial value is 2, which decreases linearly to 0 with the number of iterations; This represents a random number within the range (0, 2). Indicates the absolute value symbol; S21222, When randomly selecting the feature information of the legal resource retrieval platform that matches the user's professional role type identification information and the user's legal resource demand type judgment information, When searching for the location of an individual whale on a legal resource platform, the formula for updating the location of that whale is as follows: ,in This represents the feature information matrix of a randomly selected legal resource platform search whale individual on the legal resource retrieval platform after the t-th iteration. The position in the search space; when When the value is less than 1, the search whale on the legal resource platform chooses to swim towards the optimal search whale on the legal resource platform, that is, within the feature information matrix of the legal resource retrieval platform. Search the search space to find the legal resource retrieval platform feature information that best matches the user's professional role type identification information and the user's legal resource need type judgment information. ; when When ≥1, the individual whale searching on the legal resource platform chooses to swim towards the random individual whale searching on the legal resource platform, that is, the individual whale searching on the legal resource platform is in the feature information matrix of the legal resource retrieval platform. Randomly search the search space for the legal resource retrieval platform feature information that matches the user's professional role type identification information and the user's legal resource need type judgment information. ; S2123, BubbleNet stage, legal resource platform search whale individuals in the legal resource retrieval platform feature information matrix When hunting, they expel bubbles to form a bubble net to drive away prey, matching the user's professional role type identification information and the user's legal resource need type judgment information with the legal resource retrieval platform feature information. The legal resource platform uses a bubble network to search for whales, matching the user's professional role type identification information and the user's legal resource need type judgment information with the legal resource retrieval platform's feature information. The prey, the legal resource platform searches for individual whales, constantly updating their own feature information matrix on the legal resource retrieval platform. The location within the search space, when using BubbleNet; the formula for updating the location of individual whales on the legal resource platform is as follows: ,in This represents a random number within the range [-1, 1]. Indicated by base The exponent; Total angle value of bubble mesh, This indicates the number of bubble wrap elements. express The cosine value; S2124. When the maximum iteration algorithm is satisfied, output the feature information of the legal resource retrieval platform that matches the user's professional role type identification information and the user's legal resource demand type judgment information. ; S2125. The legal resource retrieval platform feature information output in step S2124. Information is generated through data identification and filtering by the target legal resource retrieval platform.

[0011] Preferably, the process of constructing a legal resource scheduling index based on the user's legal resource needs and the selected legal resource retrieval platform features, and executing legal resource scheduling operations to obtain real-time legal resource scheduling feedback information includes the following steps: S31. Combine and identify the user's legal resource demand characteristics information and the target legal resource retrieval platform's filtering information to construct legal resource scheduling index information; S32. Execute legal resource scheduling operation based on the legal resource scheduling index information to obtain real-time legal resource scheduling feedback information.

[0012] Preferably, the process of performing legal resource scheduling operations based on the legal resource scheduling index information to obtain real-time legal resource scheduling feedback information includes the following steps: S321. Enter the legal resource scheduling index information online in the dialog box of the Internet search platform. The Internet search platform searches for the corresponding legal resource retrieval platform based on the legal resource scheduling index information and imports the user's legal resource demand information into the dialog box of the legal resource retrieval platform. The legal resource retrieval platform retrieves the text, image, and video data related to legal resources required by the user online based on the user's legal resource demand information and obtains real-time scheduling feedback information of legal resources. The Internet search platform includes any one of Baidu search platform, Google search platform, and 360 search platform.

[0013] An AI-based legal resource scheduling system is used to implement the AI-based legal resource scheduling method. The system includes a legal resource scheduling preprocessing module, a legal resource scheduling platform analysis module, and a legal resource scheduling search module. The legal resource scheduling preprocessing module includes a user occupational characteristic information collection unit, a user legal resource demand characteristic information collection unit, a standard occupational characteristic information storage unit for different user occupational roles, a user occupational role analysis unit, a standard characteristic information storage unit for different user legal resources, and a user legal resource demand type judgment unit. The user occupational characteristic information collection unit collects user occupational characteristic information through a data input dialog box; the user legal resource demand characteristic information collection unit collects user legal resource demand characteristic information through a data input dialog box; the standard occupational characteristic information storage unit for different user occupational roles stores standard occupational characteristic information for different user occupational roles; the user occupational role analysis unit performs occupational role type identification processing based on the user occupational characteristic information and the standard occupational characteristic information for different user occupational roles to obtain user occupational role type identification information; the standard characteristic information storage unit for different user legal resources stores standard characteristic information for different user legal resources; the user legal resource demand type judgment unit performs legal resource demand type judgment processing based on the user legal resource demand characteristic information and the standard characteristic information for different user legal resources to obtain user legal resource demand type judgment information. The analysis module of the legal resource scheduling platform includes a feature information storage unit for the legal resource retrieval platform, a filtering unit for the legal resource retrieval platform, and a matching result output unit for the legal resource retrieval platform. The legal resource retrieval platform feature information storage unit is used to store legal resource retrieval platform feature information; the legal resource retrieval platform filtering unit performs filtering processing on the legal resource retrieval platform required by the user based on the user's professional role type identification information, the user's legal resource demand type judgment information, and the legal resource retrieval platform feature information, to obtain target legal resource retrieval platform filtering information; the legal resource retrieval platform matching result output unit performs the legal resource retrieval platform filtering result output operation based on the target legal resource retrieval platform filtering information and in conjunction with the display screen. The legal resource scheduling and search module includes a legal resource scheduling index information construction unit and a legal resource scheduling execution unit; The legal resource scheduling index information construction unit constructs legal resource scheduling index information by combining and identifying data based on the user's legal resource demand characteristics information and the target legal resource retrieval platform's filtering information; the legal resource scheduling execution unit executes legal resource scheduling operations based on the legal resource scheduling index information and in conjunction with the Internet search platform to obtain real-time legal resource scheduling feedback information.

[0014] (III) Beneficial Effects This invention provides an AI-based legal resource scheduling method and system. It has the following beneficial effects: First, the system accurately collects user occupational characteristics and legal resource needs through a data input dialog box, providing real data support for the subsequent precise selection of legal resource retrieval platforms. Based on user occupational characteristics and legal resource needs, combined with intelligent search algorithms, the system scientifically and efficiently analyzes the user's occupational role type and required legal resource type, enabling precise and efficient search of legal resource information based on the user's legal resource needs scenario, thereby improving the accuracy and reliability of legal resource allocation.

[0015] Second, by combining user professional role type identification information and user legal resource demand type judgment information with AI intelligent algorithms and scientifically preset legal resource retrieval platform feature information, the system intelligently filters users' legal resource retrieval platforms. At the same time, the system displays the filtering results of the legal resource retrieval platforms in a timely and visual manner. This enables customized and reliable matching of legal resource retrieval platforms based on user professional characteristics and legal resource needs, and provides intuitive and efficient output. This improves the accuracy of legal resource scheduling and user experience, and enhances the quality and efficiency of legal resource retrieval.

[0016] Third, by scientifically and promptly constructing a legal resource scheduling index based on user legal resource demand characteristics, information filtered by target legal resource retrieval platforms, and combined with data processing, and by combining with internet search platforms, users can accurately retrieve the legal resource data they need, thereby achieving customized and precise retrieval of legal resources and improving the response efficiency and satisfaction of legal resource scheduling. Attached Figure Description

[0017] Figure 1 A schematic diagram of a module of an AI-based legal resource scheduling system provided by the present invention; Figure 2 The flowchart illustrates an AI-based legal resource scheduling method provided by this invention. Detailed Implementation

[0018] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0019] An example of an AI-based legal resource allocation method and system is as follows: Example

[0020] Please see Figures 1-2An AI-based legal resource allocation method, comprising the following steps: S1. Collect user occupational characteristic information and user legal resource demand characteristic information, identify the user's occupational role type, and obtain user occupational role type identification information; process the user's legal resource demand type to obtain user legal resource demand type judgment information. S2. Based on the user's professional role type and legal resource needs type, filter out the legal resource search platforms required by the user, obtain the target legal resource search platform filtering information and output it; S3. Based on the user's legal resource needs information and the selected legal resource retrieval platform feature information, construct legal resource scheduling index information and execute legal resource scheduling operations to obtain real-time legal resource scheduling feedback information.

[0021] For further details, please refer to Figures 1-2 The process involves collecting user occupational characteristic information and user legal resource demand characteristic information to identify the user's occupational role type and obtain user occupational role type identification information; and then processing the user's legal resource demand type to obtain user legal resource demand type judgment information, including the following steps: S11. Collect the text information describing the specific job characteristics of the user's occupation online through the data input dialog box, and obtain the user's occupational characteristic information; the user's occupational characteristic information includes occupational name characteristic information, occupational level characteristic information, occupational skill characteristic information, and job nature characteristic information; The system collects the textual information of legal resources required by users online through a data input dialog box, and obtains the user's legal resource demand characteristic information, which includes the specific type of legal resources required by the user and the specific scenario description of the legal event. S12. Based on the user's occupational characteristic information and the standard occupational characteristic information set of different user occupational roles, perform user occupational role type identification processing to obtain user occupational role type identification information. S13. Based on the user's legal resource demand characteristic information and the user's different legal resource standard characteristic information set, perform user legal resource demand type judgment processing to obtain user legal resource demand type judgment information.

[0022] Based on user occupational characteristic information and standard occupational characteristic information sets for different user occupational roles, user occupational role type identification processing is performed to obtain user occupational role type identification information, including the following steps: S121. Construct a standard occupational characteristic information set for different user occupational roles. ,in Indicates the first The standard occupational characteristic information for different user occupational roles corresponds to various user occupational role types, including lawyer, corporate legal counsel, accountant, teacher, and mechanical engineer; the standard occupational characteristic information for different user occupational roles represents the standard occupational characteristic text information set for different user occupational role types; S122. Use the Word2Vec text search algorithm to combine user occupational characteristic information with standard occupational characteristic information sets for different user occupational roles. Standard professional characteristics information for different user professional roles Perform occupational characteristic text information matching to search for standard occupational characteristic information of different user occupational roles that match the user's occupational characteristic information. The corresponding user job role type text information is obtained, and user job role type identification information is obtained.

[0023] Based on the user's legal resource demand characteristics and the user's different legal resource standard characteristics, the user's legal resource demand type is determined, and the user's legal resource demand type determination information includes the following steps: S131. Construct a set of standard feature information of different legal resources for users. ,in Indicates the first The user's different legal resource standard feature information corresponds to different types of legal resources. The legal resource types include laws and regulations, legal cases, and legal documents. The user's different legal resource standard feature information represents the standard legal resource feature text information set for different types of legal resources. S132. Use the GloVe text search algorithm to combine user legal resource demand feature information with user's different legal resource standard feature information sets. Different legal resource standard characteristics information for Chinese users Perform legal resource feature character analysis to search for different legal resource standard feature information that matches the user's legal resource needs feature information. The corresponding legal resource type text information is obtained, and the user's legal resource requirement type judgment information is obtained.

[0024] By employing a user occupational characteristic information collection unit and a user legal resource demand characteristic information collection unit in tandem, and using a data input dialog box, user occupational characteristic information and user legal resource demand characteristic information are accurately collected, providing real data support for the subsequent accurate selection of legal resource retrieval platforms. The user occupational role analysis unit and the user legal resource demand type judgment unit work together to scientifically and efficiently analyze the user's occupational role type and required legal resource type based on user occupational characteristic information and user legal resource demand characteristic information combined with intelligent search algorithms. This enables accurate and efficient search of legal resource information based on user legal resource demand scenarios, improving the accuracy and reliability of legal resource allocation.

[0025] For further details, please refer to Figures 1-2 Based on the user's professional role type and legal resource needs, the system filters out the legal resource search platforms the user requires, obtains the target legal resource search platform filtering information, and outputs the following steps: S21. Based on the user's professional role type identification information, the user's legal resource demand type judgment information and the legal resource retrieval platform feature information matrix, the user's required legal resource retrieval platform is screened to obtain the target legal resource retrieval platform screening information. S22. Output the generated target legal resource retrieval platform filtering information to the display screen and perform the legal resource retrieval platform filtering result output operation.

[0026] Based on user professional role type identification information, user legal resource need type judgment information, and legal resource retrieval platform feature information matrix, the user's required legal resource retrieval platform is filtered to obtain target legal resource retrieval platform filtering information, including the following steps: S211. Constructing a feature information matrix for a legal resource retrieval platform. ,in Indicates the first This document describes the characteristic information of legal resource retrieval platforms corresponding to different types of legal resource demand scenarios. The legal resource demand scenario type is represented by an index data type formed by combining user professional role information and legal resource demand type information to filter legal resource retrieval platforms. The legal resource retrieval platform characteristic information represents the characteristic text information of the optimal legal resource retrieval platform set for different legal resource demand scenario types. The legal resource retrieval platform characteristic information includes name, website, establishment time, and a brief description of the data resource content. The legal resource retrieval platforms include Peking University Law Database, Weike Xianxing, Faxin, and LexisNexis. S212, Integrate user professional role type identification information, user legal resource demand type judgment information, and legal resource retrieval platform feature information matrix. Feature information of Chinese legal resource retrieval platform By performing keyword matching based on user professional role type and legal resource type, the search retrieves feature information of legal resource retrieval platforms corresponding to user professional role type identification information and user legal resource need type judgment information. The specific steps for constructing the target legal resource retrieval platform's filtering information are as follows: S2121, Initialization Phase: In the feature information matrix of the legal resource retrieval platform... The search space of the legal resource platform is updated with the whale population location and the maximum iteration algorithm T. The formula for updating the whale population location in the legal resource platform search is as follows: ,in This indicates a search for individual whales on a legal resource platform. Feature information matrix of legal resource retrieval platform The location in the search space, and These represent the feature information matrix of individual whales on the legal resource platform search platform. The upper and lower bounds in the search space, Indicates the value Random numbers within the interval; S2122, Encirclement of Prey Stage: The legal resource platform searches for individual whales within the legal resource retrieval platform's feature information matrix. The search space encompasses the search for legal resource retrieval platform features that match user professional role type identification information and user legal resource need type judgment information. When hunting, it will choose to target legal resource retrieval platforms whose features best match the user's professional role type identification information and the user's legal resource needs type identification information. The search results on the legal resource platform show the location of individual whales swimming or randomly moving towards legal resource retrieval platforms that match the user's professional role type identification information and the user's legal resource needs type identification information. Search for individual whales swimming on legal resource platforms based on their location; S21221, When selecting the legal resource retrieval platform feature information that best matches the user's professional role type identification information and the user's legal resource need type judgment information. When searching for the location of an individual whale on a legal resource platform, the formula for updating the location of that whale is as follows: ;in This indicates that after the (t+1)th iteration, the legal resource platform searches for individual whales. Feature information matrix of legal resource retrieval platform The location in the search space, This indicates that after the t-th iteration, the legal resource platform searches for individual whales. Feature information matrix of legal resource retrieval platform The location in the search space, This represents the feature information matrix of the search whale individual on the legal resource platform after the t-th iteration. The optimal position in the search space. Indicates the value Random numbers within, The initial value is 2, which decreases linearly to 0 with the number of iterations; This represents a random number within the range (0, 2). Indicates the absolute value symbol; S21222, When selecting the feature information of the legal resource retrieval platform that matches the user's professional role type identification information and the user's legal resource demand type judgment information, When searching for the location of an individual whale on a legal resource platform, the formula for updating the location of that whale is as follows: ,in This represents the feature information matrix of a randomly selected legal resource platform search whale individual on the legal resource retrieval platform after the t-th iteration. The position in the search space; when When the value is less than 1, the search whale on the legal resource platform chooses to swim towards the optimal search whale on the legal resource platform, that is, the search whale on the legal resource platform is within the feature information matrix of the legal resource retrieval platform. The search space is used to find the legal resource retrieval platform features that best match the user's professional role type identification information and the user's legal resource needs type identification information. ; when When the value is ≥1, the individual whale searching on the legal resource platform chooses to swim towards the random individual whale searching on the legal resource platform, that is, the individual whale searching on the legal resource platform swims towards the feature information matrix of the legal resource retrieval platform. The search space randomly retrieves legal resource retrieval platform feature information that matches the user's professional role type identification information and the user's legal resource need type judgment information. ; S2123, BubbleNet stage, legal resource platform search whale individuals in legal resource retrieval platform feature information matrix When hunting, they expel bubbles to form a bubble net to drive away prey. This information is relevant to the characteristics of a legal resource retrieval platform that match user professional role type identification information and user legal resource need type judgment information. The platform uses a search engine to identify "whales" (users) by matching their professional role type with their legal resource needs. The prey, the legal resource platform searches for individual whales, constantly updating their own feature information matrix on the legal resource retrieval platform. The location within the search space, when using BubbleNet; the formula for updating the location of individual whales on the legal resource platform is as follows: ,in This represents a random number within the range [-1, 1]. Indicated by base The exponent; Total angle value of bubble mesh, This indicates the number of bubble wrap elements. express The cosine value; S2124. When the maximum iteration algorithm is satisfied, output the legal resource retrieval platform feature information that matches the user's professional role type identification information and the user's legal resource demand type judgment information. ; S2125. Obtain the legal resource retrieval platform feature information output in step S2124. Information is generated through data identification and filtering by the target legal resource retrieval platform.

[0027] By combining the filtering unit and the matching result output unit of the legal resource retrieval platform, the system intelligently filters legal resource retrieval platforms based on user professional role type identification information, user legal resource demand type judgment information, AI intelligent algorithms, and scientifically preset legal resource retrieval platform feature information. At the same time, the system displays the filtering results in a timely and visual manner. This enables customized and reliable matching of legal resource retrieval platforms based on user professional characteristics and legal resource needs, and provides intuitive and efficient output. This improves the accuracy of legal resource allocation and user experience, and enhances the quality and efficiency of legal resource retrieval.

[0028] For further details, please refer to Figures 1-2 Based on users' legal resource needs and the selected legal resource retrieval platform features, a legal resource scheduling index is constructed, and a legal resource scheduling operation is executed to obtain real-time legal resource scheduling feedback information. This includes the following steps: S31. Combine and identify user legal resource demand characteristics and target legal resource retrieval platform filtering information to construct legal resource scheduling index information; S32. Execute legal resource scheduling operations based on legal resource scheduling index information to obtain real-time legal resource scheduling feedback information.

[0029] The process of executing legal resource scheduling operations based on legal resource scheduling index information and obtaining real-time legal resource scheduling feedback information includes the following steps: S321. Enter legal resource scheduling index information online in the dialog box of the Internet search platform. The Internet search platform searches for the corresponding legal resource retrieval platform based on the legal resource scheduling index information and imports the user's legal resource demand information into the dialog box of the legal resource retrieval platform. The legal resource retrieval platform retrieves the text, image, and video data related to legal resources required by the user online based on the user's legal resource demand information and obtains real-time legal resource scheduling feedback information. The Internet search platform includes any one of Baidu search platform, Google search platform, and 360 search platform.

[0030] By cooperating with the legal resource scheduling index information construction unit and the legal resource scheduling execution unit, the legal resource scheduling index information is scientifically and timely constructed based on the user's legal resource demand characteristics, the information filtered by the target legal resource retrieval platform, and combined with data processing. At the same time, it is combined with the Internet search platform to realize the accurate retrieval of the legal resource data required by the user, realize customized and accurate retrieval of legal resources, and improve the response efficiency and satisfaction of legal resource scheduling. Example

[0031] Please see Figures 1-2 An AI-based legal resource scheduling system is used to implement an AI-based legal resource scheduling method. The system includes a legal resource scheduling preprocessing module, a legal resource scheduling platform analysis module, and a legal resource scheduling search module. The legal resource scheduling preprocessing module includes a user occupational characteristic information collection unit, a user legal resource demand characteristic information collection unit, a standard occupational characteristic information storage unit for different user occupational roles, a user occupational role analysis unit, a standard characteristic information storage unit for different user legal resources, and a user legal resource demand type judgment unit. The user occupational characteristic information collection unit collects user occupational characteristic information through a data input dialog box; the user legal resource demand characteristic information collection unit collects user legal resource demand characteristic information through a data input dialog box; the standard occupational characteristic information storage unit for different user occupational roles stores standard occupational characteristic information for different user occupational roles; the user occupational role analysis unit performs occupational role type identification processing based on user occupational characteristic information and standard occupational characteristic information for different user occupational roles to obtain user occupational role type identification information; the standard characteristic information storage unit for different user legal resources stores standard characteristic information for different user legal resources; and the user legal resource demand type judgment unit performs legal resource demand type judgment processing based on user legal resource demand characteristic information and standard characteristic information for different user legal resources to obtain user legal resource demand type judgment information. The analysis module of the legal resource scheduling platform includes a feature information storage unit for the legal resource retrieval platform, a filtering unit for the legal resource retrieval platform, and a matching result output unit for the legal resource retrieval platform. The legal resource retrieval platform feature information storage unit stores feature information of the legal resource retrieval platform; the legal resource retrieval platform filtering unit filters the legal resource retrieval platforms required by the user based on the user's professional role type identification information, user legal resource demand type judgment information, and legal resource retrieval platform feature information, to obtain target legal resource retrieval platform filtering information; the legal resource retrieval platform matching result output unit outputs the legal resource retrieval platform filtering results based on the target legal resource retrieval platform filtering information and in conjunction with the display screen. The legal resource scheduling and search module includes a legal resource scheduling index information construction unit and a legal resource scheduling execution unit; The legal resource scheduling index information construction unit constructs legal resource scheduling index information by combining and identifying data based on user legal resource demand characteristics and target legal resource retrieval platform filtering information; the legal resource scheduling execution unit executes legal resource scheduling operations based on the legal resource scheduling index information and in conjunction with the Internet search platform, and obtains real-time legal resource scheduling feedback information.

[0032] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the appended claims and their equivalents.

Claims

1. An AI-based legal resource scheduling method, characterized in that, The method includes the following steps: S1. Collect user occupational characteristic information and user legal resource demand characteristic information, identify the user's occupational role type, and obtain user occupational role type identification information; process the user's legal resource demand type to obtain user legal resource demand type judgment information. S2. Based on the user's professional role type and legal resource needs type, filter out the legal resource search platforms required by the user, obtain the target legal resource search platform filtering information and output it; S3. Based on the user's legal resource needs information and the selected legal resource retrieval platform feature information, construct legal resource scheduling index information and execute legal resource scheduling operations to obtain real-time legal resource scheduling feedback information.

2. The AI-based legal resource scheduling method according to claim 1, characterized in that: S1 includes the following steps: S11. Collect the text information describing the specific job characteristics of the user's occupation online through the data input dialog box, and obtain the user's occupation characteristic information; The system collects textual information about the legal resources required by the user online through a data input dialog box, and obtains information about the user's legal resource needs. S12. Based on the user's occupational characteristic information and the standard occupational characteristic information set of different user occupational roles, perform user occupational role type identification processing to obtain user occupational role type identification information. S13. Based on the user's legal resource demand characteristic information and the user's different legal resource standard characteristic information set, perform user legal resource demand type judgment processing to obtain user legal resource demand type judgment information.

3. The AI-based legal resource scheduling method according to claim 2, characterized in that: S12 includes the following steps: S121. Construct a standard occupational characteristic information set for different user occupational roles. The include ;in Indicates the first Standard occupational characteristic information for different user occupational roles corresponding to various user occupational role types; S122. Using the Word2Vec text search algorithm, the user's occupational characteristic information is compared with the... The above Perform occupational characteristic text information matching to search for the text that matches the user's occupational characteristic information. The corresponding user job role type text information is obtained, and user job role type identification information is obtained.

4. The AI-based legal resource scheduling method according to claim 3, characterized in that: S13 includes the following steps: S131. Construct a set of standard feature information of different legal resources for users. The include ;in Indicates the first Different legal resource standard feature information for users corresponding to different types of legal resources; S132. Using the GloVe text search algorithm, the user's legal resource demand feature information is compared with the... The above Perform legal resource feature character analysis to search for the legal resource needs feature information that matches the user's needs. The corresponding legal resource type text information is obtained, and the user's legal resource requirement type judgment information is obtained.

5. The AI-based legal resource scheduling method according to claim 4, characterized in that: S2 includes the following steps: S21. Based on the user's professional role type identification information, the user's legal resource demand type judgment information, and the legal resource retrieval platform feature information matrix, perform the filtering process for the legal resource retrieval platform required by the user to obtain the target legal resource retrieval platform filtering information. S22. Output the generated target legal resource retrieval platform filtering information through the display screen and perform the legal resource retrieval platform filtering result output operation.

6. The AI-based legal resource scheduling method according to claim 5, characterized in that: S21 includes the following steps: S211. Constructing a feature information matrix for a legal resource retrieval platform. The include ;in Indicates the first The legal resource demand scenario type corresponds to the feature information of the legal resource retrieval platform. The legal resource demand scenario type is mainly composed of user's professional role type information and legal resource demand type information, which are combined to form the index data type used to filter out legal resource retrieval platforms. S212, Combine the user's professional role type identification information and the user's legal resource demand type judgment information with the... The above Perform keyword matching for user professional role type and legal resource type to search for the user professional role type identification information and the user legal resource demand type judgment information corresponding to the keywords. The specific steps for constructing the target legal resource retrieval platform's filtering information are as follows: S2121, Initialization phase, in the... The search space is updated with the location of whale populations and the maximum iteration algorithm T from the legal resource platform search. S2122, The prey-encirclement stage: Legal resource platforms search for individual whales as described in... Search the search space for information that matches the user's professional role type identification information and the user's legal resource need type judgment information. When hunting, it will choose to target the user whose professional role type identification information and legal resource need type judgment information best match the target. The location is where the legal resource platform searches for individual whales swimming or randomly selects whales that match the user's professional role type identification information and the user's legal resource need type judgment information. Search for individual whales swimming on legal resource platforms based on their location; S21221, When selecting the option that best matches the user's professional role type identification information and the user's legal resource need type judgment information. When searching for individual whales swimming on legal resource platforms based on their location; S21222, When randomly selecting the user's professional role type identification information and the user's legal resource demand type judgment information that match the user's professional role type identification information, When searching for individual whales on the legal resource platform, the location of the individual whales will be updated. when When the value is less than 1, the individual whale searching on the legal resource platform chooses to swim towards the optimal individual whale searching on the legal resource platform, that is, when the individual whale searching on the legal resource platform is described in the above... Search the search space to find the user whose professional role type identification information and legal resource need type judgment information best match the user's professional role type identification information and legal resource need type judgment information. ,in Indicates the value Random numbers within, The initial value is 2, which decreases linearly to 0 with the number of iterations; when When ≥1, the individual whale on the legal resource platform chooses to swim towards the random individual whale on the legal resource platform, that is, the individual whale on the legal resource platform swims towards the random individual whale on the legal resource platform. Randomly search the search space to find the user's professional role type identification information and the user's legal resource need type judgment information that match the user's professional role type identification information and the user's legal resource need type judgment information. ; S2123, BubbleNet stage, legal resource platform search for whale individuals mentioned above When hunting, they expel bubbles to form a bubble net to drive away prey that matches the user's professional role type identification information and the user's legal resource need type judgment information. The prey, the legal resource platform searches for whales using bubble networks to drive away users whose professional role type identification information and legal resource need type judgment information match. The prey, legal resource platform searches for individual whales, constantly updating their own information. The location within the search space, when using BubbleNet; updating the location of individual whales when searching on legal resource platforms; S2124. When the maximum iteration algorithm is satisfied, output the value that matches the user's professional role type identification information and the user's legal resource demand type judgment information. ; S2125, The output of step S2124 Information is generated through data identification and filtering by the target legal resource retrieval platform.

7. The AI-based legal resource scheduling method according to claim 6, characterized in that: S3 includes the following steps: S31. Combine and identify the user's legal resource demand characteristics information and the target legal resource retrieval platform's filtering information to construct legal resource scheduling index information; S32. Execute legal resource scheduling operation based on the legal resource scheduling index information to obtain real-time legal resource scheduling feedback information.

8. The AI-based legal resource scheduling method according to claim 7, characterized in that: S32 includes the following steps: S321. Enter the legal resource scheduling index information online in the dialog box of the Internet search platform. The Internet search platform searches for the corresponding legal resource retrieval platform based on the legal resource scheduling index information and imports the user's legal resource demand information into the dialog box of the legal resource retrieval platform. The legal resource retrieval platform retrieves the text, image and video data related to legal resources required by the user online based on the user's legal resource demand information and obtains real-time scheduling feedback information of legal resources.

9. An AI-based legal resource scheduling system, used to implement the AI-based legal resource scheduling method according to any one of claims 1-8, characterized in that: The system includes a legal resource scheduling preprocessing module, a legal resource scheduling platform analysis module, and a legal resource scheduling search module.

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