RETRACTED ARTICLE: Building the electronic evidence analysis model based on association rule mining and FP-growth algorithm

Abstract

In China’s criminal procedure law, electronic data is a kind of independent evidence. With the development of big data technology, more and more attention has been paid to the examination and application of electronic evidence in criminal trials. In order to obtain hidden knowledge from confused electronic evidence, an electronic evidence analysis model based on data mining is proposed. The main research is to apply the association rule technology of data mining to the analysis of electronic evidence, analyze the shortcomings of the existing association rule mining algorithm, and put forward the improved algorithm of the existing algorithm and a new idea of the algorithm. Based on FP-growth algorithm, an improved algorithm (ISPO-tree algorithm) is put forward and the theoretical proof is given. This algorithm only needs to browse the database once and adds the function of supporting a small amount of modified evidence. This algorithm improves the time efficiency of data pre-processing by making similar rules to make unequal attribute values equal and can mine more association rules under the optimum conditions of support and redundancy, and it improves the effectiveness of electronic evidence and the accuracy of criminal trial.