Intelligent Examination Method of Crimi-nal Evidence based on Association Rules

Zhi Xu

School of Public Security, Northwest University of Political Science and Law, Xi'an, 710063, China

Abstract: Conventional review methods have the problem of unclear data classification, which leads to the weak relevance of data sets. This paper designs an intelligent review method of criminal evidence based on association rules. Extract the logical features of criminal evidence, combined with the interaction between da-ta information, construct the evidence text classification model based on association rules, calculate the data mean value in the super rectangle, cluster the evidence data set information, and set the intelligent review mode according to the hidden vector feature label. Experimental results: the average correlation degree be-tween the intelligent examination method and the two conventional examination methods is 31.425, 23.738 and 22.197 respectively, which proves that the intelligent examination method of criminal evidence combined with association rules has better performance.

Keywords: Association rules; Criminal evidence; Review method; Data set