Triad similar task-based trial risk early warning method

A technology of risk early warning and triples, applied in the field of deep learning and natural language processing, can solve problems such as inaccurate case vectors, insufficient expressiveness of vectors, inability to encode word sequence relations, etc., to reduce manpower burden and wide adaptability , the effect of convenient reference

Active Publication Date: 2021-02-02
SHANGHAI JIAO TONG UNIV
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Problems solved by technology

The disadvantage of this technology is that the word2vec word vector training method cannot encode the sequence relationship between words into the vector, so the expressiveness of the vector is insufficient; secondly, after getting the word vector, often only a small number of keywords can be selected for the case (2-3) Calculate the case vector, so the case vector is often not accurate

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  • Triad similar task-based trial risk early warning method
  • Triad similar task-based trial risk early warning method
  • Triad similar task-based trial risk early warning method

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Embodiment Construction

[0055] The following describes several preferred embodiments of the present invention with reference to the accompanying drawings, so as to make the technical content clearer and easier to understand. The present invention can be embodied in many different forms of embodiments, and the protection scope of the present invention is not limited to the embodiments mentioned herein.

[0056] First, the terms and abbreviations involved in the embodiments are explained and explained.

[0057] Triplet similarity task: The triple similarity task refers to the calculation of the similarity of a triple , where a represents the anchor sample, p represents the positive sample, and n represents the negative sample. In the scenario of legal document similarity matching, the anchor sample is the legal document that needs to be queried, while the positive sample indicates the legal document that is relatively similar to the anchor sample, and the negative sample indicates the legal document th...

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Abstract

The invention discloses a triad similar task-based trial risk early warning method, and the method comprises the following steps: acquiring data from a legal document database, performing keyword matching, and extracting case description and a judgment result; carrying out the text preprocessing, including word segmentation, data enhancement and other operations, and generating multiple triples; generating a case vector by using an LSTM network, and carrying out triple similar task judgment to obtain a representation model of the case; preprocessing the current case and the historical case respectively and inputting the preprocessed cases into a representation model to obtain respective case representations; calculating a topM case with the highest similarity, obtaining a judgment result representation of the topM case, and finally calculating the similarity between the result and the judgment result of the current case to obtain a deviation risk value. According to the method, the current legal document can be analyzed in a triple similarity calculation mode, and the case with relatively high similarity is found out from the historical electronic case. A recommended judgment rangeis given according to the judgment result of the past case, thereby achieving the purpose of trial deviation early warning.

Description

technical field [0001] The invention relates to the fields of deep learning and natural language processing, in particular to a trial risk early warning method based on triple similarity tasks. Background technique [0002] In the era of big data, artificial intelligence has a wide range of applications in various industries. In the construction of smart courts, by giving machines the ability to understand legal texts and applying artificial intelligence technology in the judicial field, it can provide judicial staff with intelligent assistance systems such as case understanding, sentencing assistance, and risk warning, which can effectively improve the efficiency of court trials. , and improve the quality of judgments, and promote the intelligentization of trials, enforcement, and services through information technology. By making full use of the cutting-edge technology of artificial intelligence, it analyzes, processes, and classifies the information marked in electronic ...

Claims

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Application Information

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IPC IPC(8): G06Q50/18G06Q10/06G06N3/04G06K9/62G06F40/194G06F16/335
CPCG06Q50/18G06Q10/0635G06F40/194G06F16/335G06N3/044G06N3/045G06F18/214
Inventor 王晓燕潘理刘宁
Owner SHANGHAI JIAO TONG UNIV
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