Multi-party evidence association model construction method based on Bayesian network and evidence chain extraction method and device

Abstract

The invention provides a multi-party evidence association model construction method based on a Bayesian network and an evidence chain extraction method and device. The method comprises evidence network construction based on a fact judgment chain, evidence weight calculation and an evidence chain reasoning method based on a Bayesian network. Evidence sources are divided into original evidences, informed evidences, judicial expertise evidences, third-party evidences and the like. Firstly, a multi-party evidence association network is constructed, each evidence entity serves as a node in the network, and the correlation probability between the nodes in the network is calculated based on the association relationship between the evidence elements; then, based on the evidence type of the event judgment chain, a multi-party evidence association model based on the Bayesian network is constructed; and finally, the Bayesian network is optimized by adopting a genetic algorithm to obtain a credible evidence chain. According to the method, the evidence chain with the maximum credibility can be found from multiple sources, and judicial personnel are helped to screen the credible evidence chain from multi-party certification or contradictory evidences.

Description

technical field [0001] The invention belongs to the field of artificial intelligence and judicial big data, and specifically relates to a Bayesian network-based multi-party evidence association model construction method and evidence chain extraction method and device. Background technique [0002] As the public's awareness of the rule of law increases, the judicial needs of the people are diversified, and new requirements are put forward for the comprehensiveness of information, the sense of distance in communication, and the timeliness of interaction. Courts at all levels are facing enormous pressure on litigation services, and limited resources are difficult to meet all the demands of different groups of people. Providing convenient litigation services for the public is an important function of the construction of "smart courts", and the review of evidence from multiple parties in a case and the determination of evidence chains are the core of litigation services. [0003...

AI Technical Summary

Problems solved by technology

Many reasoning problems are based on the method of rule judgment, and the rule set is usually complex and huge, requiring manual construction and dynamic maintenance

At the same time, rule-based methods cannot support dynamic and ambiguous reasoning scenarios

In the judicial litigation field, the evidence is heterogeneous and diverse, the sources of evidence are diverse, and the relationship between evidence is complex.

Rule-based methods are difficult to effectively deal with the challenge of judicial evidence relationship modeling

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