Judicial decision reasoning method based on interpretable causal model

Abstract

The invention relates to the fields of machine learning, natural language processing, causal reasoning and the like, in particular to a judicial decision reasoning method based on an interpretable causal model. The judicial decision reasoning method comprises the steps of analyzing and representing judicial data, defining a judicial decision inference framework, and constructing a judicial decision inference cause and effect model. Wherein defining of the judicial decision inference framework comprises the steps of extracting fact elements, identifying the fact elements and obtaining a decision result. The model construction comprises the steps of obtaining a reason variable, obtaining a result variable, constructing a correlation function, and constructing a judicial decision reasoning cause and effect graph. According to the judicial decision reasoning method, causal reasoning of judicial judgment is realized, and the problems that an existing judicial judgment reasoning method lacksa reasoning mechanism and is poor in interpretability can be effectively solved, and the accuracy of a case judgment result easy to confuse can be obviously improved.

Description

technical field [0001] The invention relates to the fields of machine learning, natural language processing, causal reasoning, etc., and specifically relates to a judicial decision reasoning method based on an interpretable causal model. Background technique [0002] In recent years, big data and artificial intelligence algorithms have been increasingly valued and promoted in various industries and fields. Many countries, including my country, have raised artificial intelligence to a national strategic level. In the judicial field, benefiting from the promotion of big data technology, judicial institutions at all levels in my country have entered a period of "smart court" construction with the provision of smart judicial services as the core. The "New Generation Artificial Intelligence Development Plan" issued by the State Council clearly stated: Strengthen the construction of smart courts, promote the application of artificial intelligence in evidence collection, case anal...

AI Technical Summary

Problems solved by technology

Existing related research on judicial judgments mainly uses deep learning methods, and the experimental process lacks interpretability and reasoning mechanisms. The judicial judgment reasoning causal model proposed by the present invention solves the interpretability problem of judicial judgment reasoning to a certain extent. Fair justice and justice for the people, the establishment of a fair and transparent judicial service system provides important technical support

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