16 results about "Case description" patented technology

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 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.

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 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 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.

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 application provides a case allocation handling method, device, equipment and medium, the method comprises the following steps: using a LangChain framework and a large language model to construct an intelligent acceptance system, and training the large language model of the intelligent acceptance system by using collected case data; collecting case data in real time through a data acquisition device, the case data includes case descriptions, and uploading the collected case data to the intelligent acceptance system; the intelligent acceptance system automatically accepts the received case data, uses the trained large language model to automatically classify the accepted cases, and automatically allocates the accepted cases to the handling terminal used by the handler in combination with a rule engine. The application has the advantages that the processing efficiency and accuracy of urban governance cases can be greatly improved, the complexity of manual operation is reduced, and more convenient and personalized urban governance service experiences are provided for users.

The invention provides a large model inductive deductive reasoning method, which relates to the field of large models, effectively eliminates noise samples with similar case descriptions but contrary logics through double constraints of fact recombination and category limitation, constructs determined logic representations through an FOL symbolization form, and combines a feedback-driven cause-tracing reasoning mechanism, so as to improve the reliability of the large model. And refined logic induction of case fact features is realized. The inherent defect that a large model tends to be excessively generalized based on surface semantics is effectively overcome, fact features causing conclusion differences can be captured and internalized, and accurate logic mapping from key facts to decision conclusions is established. According to the method, a dynamic balance mechanism is established between pure logic reasoning and scene intuition by introducing a semantic constraint auto-reflection strategy, the rigid limitation of a traditional deductive reasoning mechanical application rule is broken through, and the self-adaptive ability of the model to cope with exceptional plots and complex contexts is improved.

The invention provides a multi-police collaborative combat system and method based on a workflow engine, and belongs to the field of information collaboration. The problem of low police resource transfer efficiency is solved; the specific system is as follows: a data fusion module for summarizing service data and constructing a decentralized block chain network; the police strength distribution module is used for predicting the number of cases in each region and distributing police strength; the case analysis module is used for extracting and separating case description information and case judgment information corresponding to each piece of case data, and training a text model; selecting a path for the police car by combining the speed of the police car according to the positions of the police car and the crime area; through efficient sharing and collaborative analysis of multi-police information, data of related departments are rapidly processed by using big data analysis and an artificial intelligence algorithm, a scientific basis is provided for decision making of the related departments, and the case detection efficiency and the social public security prevention and control capability are improved.

The invention provides a lawyer recommendation method and device, a terminal, a server and a readable storage medium. The method comprises the following steps: determining a case description of a case involved by a user; the case description is obtained based on current consultation records and historical consultation records of the user and / or one or more of uploaded documents, images, voices and videos; performing feature extraction on the case description to obtain a feature vector capable of representing the case description; the feature vectors serve as input, and a lawyer list and a judgment case list are matched through a trained recommendation model; wherein the lawyer list is obtained by performing descending sorting on the basis of the winning probability of the case documents involved by the simulation processing user, and the judgment case list is obtained by performing descending sorting on the basis of the similarity with the case documents involved by the user. According to the method, the case description is accurately determined on the basis of a multi-data combination mode of current data, traced historical data, texts, images, voices or videos and the like, so that the recommendation model is promoted to be matched with the optimal lawyer list and judgment case list.