Legal artificial intelligence interactive platform based on text analysis and semantic grabbing technology

Abstract

A legal artificial intelligence interactive platform based on text analysis and semantic grabbing technology is compose of a text information receiving and analyzing module for recognizing problem input by user to extract keyword. A keyword accurate matching module, configured to establish a corresponding relationship between a keyword and a legal vocabulary, determine a legal vocabulary corresponding to the keyword, and generate and display an associative sentence containing the legal vocabulary according to the legal vocabulary; A multi-dimensional database matching module for analyzing a solution of generating a case; An intelligent interaction and push module is used for calculating data results and generating legal solutions according to user information and data variables input by the user. Compared with the prior art, the invention can realize intelligent and automatic solution finally by using word part-of-speech word meaning classification and combining with sentence pattern to analyze the central idea of the article. Achieving multiple aggregation of data to form potential new patterns and new data, using machine learning technology effectively; Implementation of multi-domain cross-analysis.

Description

technical field [0001] The present invention relates to a big data platform and artificial intelligence field, and aims to combine the legal field, use text analysis and semantic capture technology to realize intelligent interaction between users and machines, provide users with a complete set of solutions to legal disputes, and simplify the process. Background technique [0002] Relevant technologies in the legal field appearing on the market provide a technical platform for legal dispute resolution. The legal solutions that product introductions can provide usually only provide relevant parts of the legal provisions, and many of them are even human responses, some of which can be realized and intelligent. The realization of interactive products generally includes that users input their own questions through terminal products such as computers, and the computer matches the preset answers according to the user's questions. The answers generally include legal provisions corres...

AI Technical Summary

Problems solved by technology

[0002] Relevant technologies in the legal field appearing on the market provide a technical platform for legal dispute resolution. The legal solutions that product introductions can provide usually only provide relevant parts of the legal provisions, and many of them are even human responses, some of which can be realized and intelligent. The realization of interactive products generally includes that users input their own questions through terminal products such as computers, and the computer matches the preset answers according to the user's questions. The answers generally include legal provisions corresponding to the user's questions. Based on this, this The inventor of the invention found that the technical functions on the market today are simple and can only provide relevant legal provisions through keyword matching, but cannot really provide a complete set of dispute solutions, such as calculating the amount of compensation for the dispute case, let alone provide users with private information. Customized specific advice, the information disclosed in this background technology section is only intended to increase the understanding of the general background of the present invention, and should not be considered as an acknowledgment or in any form to imply that the information constitutes what is already known to those of ordinary skill in the art current technology

[0003] The deficiencies of today's products are obvious: First, it is self-contained, but not authoritative, and cannot be qualified to accurately locate the segmented areas of user legal disputes

Second, it is technically impossible to realize intelligent solutions

Third, the data cannot be aggregated multiple times to form potential new models and new data (the machine learning technology cannot be used effectively)

Fourth, it is impossible to achieve multi-field cross-analysis

Fifth, it is not automation at all, it is intelligent, and it is basically still manual participation

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