37 results about "Case description" patented technology

The invention discloses a structured legal document generation method and system based on large model and knowledge base enhancement, and belongs to the field of structured legal document generation. The method comprises the following steps: acquiring a case description and an official document type according to user input; retrieving a law and regulation knowledge base based on the case description to obtain an associated law article set related to the case description; retrieving a legal official document template knowledge base based on the official document type to obtain a legal official document template set related to the official document type; under the condition that a legal official document template which is suitable for case description and consistent with the type of the official document exists in the legal official document template set, generating a legal official document input by the user based on the user input, the associated law article set and the legal official document template; otherwise, performing network search according to the document type to generate the structured legal document. According to the method, the readability of the legal official document can be improved, and more intuitive reading experience is provided for a user.

The invention discloses a litigation strategy generation and complaint rate prediction method based on multi-modal data fusion and intelligent reasoning. The method aims at improving the efficiency and pertinence of legal consultation. Case description and evidence files are analyzed by means of natural language processing, an OCR (optical character recognition) technology, image recognition and the like, and a comprehensive solution of complaint risk early warning, litigation request recommendation and complaint rate prediction can be realized by the method in combination with a dynamic knowledge graph and a probability graph model constructed by a historical judgment database. Specifically, the system firstly analyzes case information and related evidences input by a user through NLP, OCR and image recognition technologies, then constructs a dynamic knowledge graph based on the information, and analyzes a case in a manner of aligning with the dynamic knowledge graph. Then, through comparison of historical discriminant data, the system can generate a complaint risk early warning, recommend a corresponding litigation request, and predict a complaint rate and influence factors thereof based on a probabilistic graph model and a path reasoning method. In addition, the method also emphasizes the interpretability of a prediction result, and helps a user to understand a prediction basis through knowledge graph path visualization and an LIME algorithm.

The invention belongs to the technical field of computer networks, and provides a method for finding lawyers online. In order to solve the problem that a traditional lawyer finding mode is inaccurate in matching, case description and files are received through a user input module, and preprocessing, semantic understanding and key information extraction are carried out; the dialogue interaction module obtains legal service demand information through multiple rounds of interaction; the law office-lawyer-judgment document database stores lawyer agent historical case information; the lawyer recommendation module combines various methods to calculate similarity scores, screens out judgment documents with good case results, recommends lawyers, and displays information such as lawyer agent fees; and the charging mode management module realizes the unified setting of the charging function. According to the method, various artificial intelligence technologies are comprehensively applied, efficient and accurate lawyer recommendation service is provided for the user, the matching efficiency is improved, and the transparency and reliability of the recommendation process are enhanced.

The invention provides a legal clause recommendation method, electronic equipment and a program product. The legal clause recommendation method comprises the steps that a collected legal text is analyzed based on a large legal language model in the vertical field, a legal knowledge dynamic graph is generated, and the legal knowledge dynamic graph comprises the logic relation, the conflict relation and the dynamic revision relation between legal clauses; nodes in the legal knowledge dynamic graph are labeled with timeliness tags and regional tags; performing judicial logic reasoning on the received case description according to the law big language model and the law knowledge dynamic graph, and determining a target law clause matched with the case description; based on a weight adjustment factor, a weight value corresponding to the target legal clause is determined, and the weight adjustment factor is used for describing the association degree between the target legal clause and the case description; and generating a legal clause recommendation report according to the weight value corresponding to the target legal clause.

The application discloses a structured legal document generation method and system based on a large model and a knowledge base enhancement, and belongs to the field of structured legal document generation. The method comprises the following steps: acquiring a case description and a document type according to user input; retrieving a legal regulation knowledge base based on the case description to obtain a relevant law article set related to the case description; retrieving a legal document template knowledge base based on the document type to obtain a legal document template set related to the document type; in the case that there is a legal document template suitable for the case description and consistent with the document type in the legal document template set, generating a legal document of the user input based on the user input, the relevant law article set and the legal document template; otherwise, performing network search according to the document type to generate a structured legal document. The application can improve the readability of the legal document and provide a more intuitive reading experience for the user.

The invention relates to a case legal clause auxiliary recommendation method, system and device and a medium. The method comprises the following steps: according to a case description text input by a user, performing legal element extraction on the case description text to obtain case element data; obtaining a case feature vector by combining a preset legal concept ontology library and the case element data; generating an initial provision set based on the case feature vector and a preset legal provision knowledge graph; obtaining a legal provision sorting list according to the case feature vector and the initial provision set; and obtaining a legal provision recommendation result based on the legal provision sorting list. By adopting the method, case semantic features can be deeply understood, the accuracy and integrity of legal provision recommendation are improved, the pertinence of applicable situation analysis is effectively enhanced, and efficient and reliable intelligent auxiliary support is provided for legal practice.

The invention relates to a multi-modal evidence chain analysis method and system, and the method comprises the steps: determining a case description word set based on a case basic report, querying an associated evidence event set in a multi-modal evidence event set based on the case description word set, carrying out the pairwise combination correlation analysis of the associated evidence events in the associated evidence event set, and obtaining a multi-modal evidence chain analysis result; identifying a high association value set in the content association value set, identifying a center association value set corresponding to the center evidence event in the high association value set, sequentially identifying a high association event of each center association value in the center association value set to obtain a target evidence chain event set, and summarizing the target evidence chain event set. And obtaining a plurality of duplicate removal evidence chain event sets. According to the invention, the efficiency and accuracy of multi-modal evidence chain analysis can be improved.

The invention provides an administrative law enforcement auxiliary system based on a large language model and a retrieval enhancement generation technology, and relates to the technical field of artificial intelligence, comprising: an analysis processing module obtains case information of a law enforcement scene, and understands and analyzes the case information through the large language model to obtain case description information; a retrieval analysis module performs associated information retrieval in a knowledge base according to the case description information based on a retrieval enhancement generation technology to obtain target analysis data; and the suggestion feedback module determines law enforcement suggestions according to the target analysis data and performs feedback display on the law enforcement suggestions in combination with the target analysis data. According to the method, a large language model and a retrieval enhancement generation technology are combined, so that law enforcement officers can efficiently look up related data by means of artificial intelligence in the actual law enforcement process, meanwhile, dependence on the ability of the law enforcement officers can be reduced, the accuracy and interpretability of law enforcement bases are improved, the decision accuracy is ensured, and the law enforcement efficiency is improved. And the fairness and consistency of law enforcement are ensured.

The invention discloses an application program generation method and device. The method comprises the following steps: acquiring use case description information, and detecting the use case description information according to a preset detection rule to obtain to-be-translated use case description information meeting the preset detection rule; and translating the to-be-translated use case description information to obtain an application program corresponding to the to-be-translated use case description information. The application program is obtained by translating the use case description information generated by the user based on the preset definition rule, so that the verification quality of the application program on chip system-level verification can be improved.

The present disclosure provides a legal clause recommendation method, an electronic device and a program product. The legal clause recommendation method of the present disclosure comprises: analyzing collected legal texts based on a vertical field legal large language model to generate a legal knowledge dynamic graph, the legal knowledge dynamic graph comprising logical relationships, conflict relationships and dynamic revision relationships between legal clauses, and the nodes in the legal knowledge dynamic graph being labeled with time-effectiveness labels and regional labels; performing judicial logical reasoning on received case descriptions according to the legal large language model and the legal knowledge dynamic graph to determine target legal clauses matching the case descriptions; determining weight values corresponding to the target legal clauses based on a weight adjustment factor, the weight adjustment factor being used to describe the degree of association between the target legal clauses and the case descriptions; and generating a legal clause recommendation report according to the weight values corresponding to the target legal clauses.

The invention relates to the technical field of legal consultation, in particular to a legal affair consultation method and system based on AI interaction. The method comprises the following steps: acquiring consultation information; analyzing the consultation information, and determining a consultant type and case description; analyzing the case description, and determining a legal subject and a dispute focus; and determining a case handling lawyer according to the legal subject, the dispute focus and the consultant type. The consultation starting efficiency is improved, the initial interaction time is shortened, meanwhile, the data availability is guaranteed, and flow interruption caused by information omission is prevented. The interference of redundant data is eliminated, the accuracy of user identification and the clarity of case content are improved, and consultation deviation caused by identity misjudgment or content mixing is reduced. Error judgment of entities is avoided, analysis errors are reduced, the case processing period is shortened, and the correlation of legal suggestions is enhanced. The lawyer matching accuracy and efficiency are improved, resource waste is reduced, and the case processing quality is enhanced.

The present application provides a method and device for matching case facts with legal provisions. The method includes: segmenting the case fact description text to generate a first phrase set; in the first phrase set, screening out a second phrase set with preset attributes; establishing a mapping of the second phrase set in a legal text database to obtain a number of legal provisions that have a mapping relationship with the second phrase set; and determining the matching degree between the case fact description text and the several legal provisions through a pre-trained Bert‑wwm coding matching model. In this way, encoding can be performed in combination with text semantics, so that when matching the case description text, matching of regulations of different granularities can be performed in combination with context semantics, thereby increasing the matching accuracy of the target regulations.

Embodiments of the present application provide a fraud identification model construction method, a fraud identification method and equipment. The method can include: obtaining a plurality of fraud case description texts; processing the plurality of fraud case description texts using a large model to obtain common feature description information corresponding to fraud cases of different types; retrieving from a modeling expert knowledge base according to the common feature description information of a target type of fraud case to obtain a modeling scheme corresponding to the target type of fraud case, wherein the modeling expert knowledge base stores a corresponding relationship between case features and modeling schemes, and the target type is any of the case types contained in the plurality of fraud cases; and constructing an identification model for fraud of the target type according to the modeling scheme. In this way, a precise identification model can be quickly constructed, and the fraud identification effect is improved.

Embodiments of the present application provide a method and device for inquiring, electronic equipment, storage medium and program product, relating to the technical field of artificial intelligence. The method comprises: obtaining case description information of an inquiring object, inputting the case description information into a large inquiring model, determining an involved case type corresponding to the case description information through the large inquiring model, generating corresponding inquiring suggestions based on the case description information and the involved case type through the large inquiring model, and inquiring the inquiring object based on the inquiring suggestions. Through the large inquiring model based on the case description information, the embodiments of the present application classify the case and generate inquiring suggestions, thereby realizing accurate inquiring, obtaining complete and accurate case information, and improving the efficiency of case handling.

The invention discloses a test case generation method and device, equipment and a medium, and relates to the field of automated tests.The test case generation method comprises the steps that an original case description document is obtained, and normalization processing is conducted on all case designs in the original case description document to obtain a normalized case description document; extracting a keyword interface from the normalized use case description document according to a test function point; wherein the keyword interface comprises a keyword function corresponding to the test function point and a corresponding function input parameter; analyzing use case step description in the normalized use case description document to match and extract corresponding parameters from the use case step description based on the keyword interface so as to generate use case test steps; and writing the case test steps into a target test case table to generate an executable test case file. According to the method and the device, the test case can be automatically generated, and the accuracy and the consistency of generating the test case are improved.

The present invention discloses a data compliance analysis method, including: setting up a legal knowledge base, a compliance questionnaire library, and an intelligent suggestion library; selecting a target law in the legal knowledge base, automatically identifying the legal provisions related to data compliance therein and making annotations; selecting a target module in the compliance questionnaire to enable the user to obtain a customized compliance questionnaire form and make selections; inputting a case description, data, and the answered compliance questionnaire into the intelligent suggestion library, analyzing the data risks and recommending several laws with the highest violation probabilities; performing form authenticity verification, violation item risk rating, and scoring of each data dimension on the answered compliance questionnaire to obtain a data compliance score.

The present application belongs to the field of information extraction, and particularly relates to a crime name prediction multi-task learning method fusing behavior words. Step 1: using BERT pre-training to obtain abstract semantic representation of text information for case description of judicial documents; Step 2: based on the abstract semantic representation of text information in step 1, using BiLSTM to obtain context semantic dependency features in the text; Step 3: based on the context semantic dependency features in step 2, recognizing the position of the text where the behavior word boundary is located in the manner of positioning the boundary; Step 4: based on the positioning of the behavior word boundary in step 3, obtaining the span of the behavior word by combination; Step 5: based on the behavior word span recognized in step 4, predicting the corresponding crime name by constructing the correlation information between the behavior words. The present application is used to solve the problem that the existing method often depends on text features, ignores the difference of behavior elements in different cases, lacks effective use of criminal behavior and the parameter information between different tasks cannot be shared.

This invention discloses a question-and-answer method, apparatus, and related equipment for case acceptance scenarios. The method receives the current case cause and case description information input by the user, and performs multi-dimensional feature recognition on the case description information to obtain multi-dimensional case feature tags; based on the case feature tags and the current case cause, it extracts corresponding question content from a pre-set question database; based on the case feature tags, it performs guided transformation on the question content to obtain guided questions; it receives the user's answer content input based on the guided questions, and performs semantic parsing on the answer content to obtain key case information; it stores the key case information in a structured manner and matches it with the core information items corresponding to the current case cause, determining the information completeness based on the information matching results; and it determines whether to continue questioning based on the information completeness. This method sets up multi-dimensional feature recognition for judicial case acceptance scenarios, which can comprehensively reflect the information quality of the parties' answers.

The disclosure provides a regulation query method and device based on a coal mine regulation knowledge graph, and relates to the technical field of coal mine safety. The method comprises the following steps: obtaining a coal mine case text to be queried, a coal mine case set and a coal mine regulation knowledge graph; calculating the semantic similarity of the case text and each historical case, and taking the obtained semantic similarity as the semantic similarity component of the corresponding regulation; calculating the graph similarity of the case text and each node of the knowledge graph to obtain the graph similarity component of each regulation; and fusing the semantic and graph similarity components to select a target regulation and generate a reply text. Through the fusion of semantic matching and graph structure association, the disclosure can accurately screen the target clauses that are closely related to the semantic of the case text and the structure from the overall regulation system, realizes end-to-end accurate query from case description to regulation matching, and significantly improves the accuracy and completeness of the regulation basis obtained in the coal mine safety supervision.

The invention belongs to the technical field of legal provision matching, and discloses a legal provision consulting device which comprises a case input module used for receiving a natural language case description text input by a user; the element extraction module is in communication connection with the case input module and is used for carrying out natural language processing on the natural language case description text so as to extract legal element information in the natural language case description text; a matching recommendation module which is in communication connection with the element extraction module and is used for calculating the correlation degree between the case description and a plurality of pre-stored legal provisions based on the extracted legal element information and screening out a target legal provision according to the correlation degree; and the result output module is in communication connection with the matching recommendation module and is used for outputting the information of the target legal provisions. According to the method, the mapping problem between the living natural language of the user and the highly refined and professional legal language is solved, the consulting difficulty is reduced, and the accuracy and the comprehensiveness of consulting the legal provisions are improved.

The method disclosed in the present invention for standardizing the storage of CFD verification and confirmation case data includes case data organization, case data collation standards, and case data storage standards; the case data collation standards include case data naming standards, case description file compilation standards, self-description file definition standards, computational grid data collation standards, computational result data collation standards, and test result data collation standards; the case data storage standards are based on the data output by the case data collation standards, using a hierarchical tree-like organizational structure that is convenient for domestic users to use, and enter the case database from the perspectives of newly created cases, basic properties, case descriptions, comparable data, extraction tools, and related documents. The technical solution provided by the present invention standardizes and ensures the quality of submitted case data, solving the problem of incomplete case data and lack of availability during the construction of a CFD verification and confirmation case library.

The present invention provides a multi - crime prediction method, including: Step 1, training a text summary model to obtain a case summary; Step 2, splicing the case description and the case summary to obtain a case encoding vector at the current time step; Step 3, encoding the vector sequence using the bidirectional language model of the UniLM model, and taking the output vectors at all positions after encoding; Step 4, calculating to obtain the case - crime attention encoding vector at the current time step; Step 5, obtaining the crime predicted at the current time step. The present invention can obtain the semantic information of each crime and the mutual relationship between crimes, and finally add a case - crime attention mechanism in the decoding process to calculate the correlation between the hidden state and all crimes in the decoding process, significantly improving the accuracy of multi - crime prediction.

The embodiment of the invention discloses a test case processing method and device, equipment and a storage medium. The method comprises the steps of obtaining a plurality of to-be-executed test cases of target software and case description information of each test case; according to test requirement contents corresponding to multiple test requirements of the target software and the case description information of each test case, performing one-by-one coverage detection on the test requirements, and determining first test requirement contents covered by the multiple test cases; determining a demand coverage rate corresponding to the plurality of test cases according to the number of the first test demand contents; and if the demand coverage rate is smaller than the preset coverage rate, performing supplementary processing on the test cases according to the second test demand content which is not covered by the plurality of test cases. Through the technical scheme of the embodiment of the invention, comprehensive detection and supplementary processing of demand coverage can be carried out on the test case, so that the comprehensiveness of software testing is improved, and the software testing efficiency is improved.

The embodiment of the invention relates to a scene reproduction method and system, electronic equipment and a computer readable storage medium. The method comprises the steps of obtaining an evidence material of a case, and generating a case description text based on the evidence material; the evidence material comprises one or more of text data, image data, audio data and video data; scene analysis information is acquired based on the case description text; generating an image and a video based on the scene analysis information; and generating a three-dimensional scene reconstruction model based on the image and the video. The generated three-dimensional scene reconstruction model is based on evidence materials such as text data, image data, audio data, video data and the like, can realize visual reproduction of case scenes, and can be applied to auxiliary case analysis in the fields of judicial, criminal investigation and the like.

The application provides a case information processing method, device and equipment. The method of the application obtains a plurality of case description files of a to-be-processed case, extracts case description texts from each case description file, divides each case description text into text segments according to the relevance of sentences in the case description text, and the sentences in the same text segment correspond to the same event. The text segments divided by the plurality of case description files are clustered according to the relevance between the text segments, a plurality of clusters are obtained, each cluster contains at least one text segment corresponding to the same event. Event information is extracted from the text segments contained in each cluster, the event information is sorted according to time elements to generate case fact information, and the case fact information is output. The case fact information can be automatically sorted from the multiple and complex case description files, the time consumed by relevant personnel in sorting the case fact is reduced, the efficiency of generating the case fact is improved, and thus the case handling efficiency can be improved.

The invention provides a judicial data access control method and device and a storage medium, and relates to the technical field of judicial data access control, and the method comprises the steps: obtaining a case description text of a target case input by a user and an applicable law article specified by the user; according to an applicable law article specified by a user, the case description text of the target case is transferred, and a transferred case description text corresponding to the target case is obtained; performing semantic feature extraction on the transcription case description text corresponding to the target case to obtain a semantic feature vector XL1 of the transcription case description text corresponding to the target case; obtaining a first similarity between the XL1 and each historical case semantic feature vector; determining the historical case corresponding to the historical case semantic feature vector of which the first similarity is greater than a preset similarity threshold as a target historical case; pushing the target historical case to the user; according to the method and the device, the matching between the retrieved historical case and the current case is relatively high.

This application relates to a training method, apparatus, computer device, and storage medium for a disease reasoning model, comprising: acquiring a synthetic phenotype set of a target disease; the synthetic phenotype set including a core phenotype subset and a candidate phenotype subset; the core phenotype subset including at least one phenotype whose qualitative frequency reaches a preset condition; the candidate phenotype subset being sampled from other phenotypes besides those in the core phenotype subset; inputting the synthetic phenotype set into a first large language model to synthesize case text, obtaining case description text, and training an initial reasoning model based on the case description text to obtain a trained reasoning model; inputting a preset case description text into the trained reasoning model for prediction, obtaining a prediction result, and retraining the trained reasoning model based on the prediction result to obtain a target reasoning model. This method can improve the reasoning accuracy of the reasoning model.

An embodiment of the present application provides a claim prediction method, apparatus, electronic device, and storage medium, belonging to the field of artificial intelligence technology. The method includes: obtaining case information data and case description data of a target case, where the case information data is used to record the basic case information of the target case, and the case description data is used to describe the case situation of the target case; extracting features from the case information data to obtain a case feature vector; performing node prediction on the case feature vector through a tree model to obtain target tree node data and a first prediction value; performing encoding processing on the case description data to obtain a target semantic hidden vector; performing prediction processing on the target tree node data and the target semantic hidden vector through a claim prediction model to obtain a second prediction value; calculating a claim based on the first prediction value and the second prediction value to obtain target claim data. The embodiment of the present application can improve the accuracy of claim situation judgment.

The invention discloses a lawyer recommendation system and method based on artificial intelligence. According to the system, user case description and evidence files are obtained, and comprehensive case characterization is generated and vectorized after processing. On one hand, case similarity scores are calculated in a vector database through mixed search; and on the other hand, the historical agent cases of the lawyers are scored through a case scoring agent. And finally, the system fuses the similarity score, the case score and the user evaluation score, generates a comprehensive score, and recommends the most suitable lawyer to the user according to the comprehensive score. According to the lawyer recommendation method, the crossing from passive matching to active evaluation is realized, and the lawyer recommendation accuracy and the intelligent level are remarkably improved.

The invention relates to a telecommunication fraud case element analysis method and device based on a language large model, and the method comprises the steps: obtaining case description data and case elements corresponding to the case description data, and constructing an initial data set; the method comprises the following steps: pre-labeling an initial data set through a prompt project to obtain a pre-labeled data set, dividing the pre-labeled data set into a plurality of subsets, and correcting a pre-labeled result in each subset to obtain a verification data set. And an instruction data set is screened out from the verification data set, the case description data in the instruction data set is used as the input of the large model, the case elements are used as the output of the large model, the large model is trained, and a case element analysis model is obtained. And selecting a plurality of case description data and case elements subjected to annotation verification to construct an evaluation data set so as to evaluate the case element analysis model. And when the evaluation is passed, inputting the current case description data into the case element analysis model, and outputting a corresponding case element analysis result.