FP-array在计算机犯罪挖掘中的应用

针对现代社会计算机犯罪中电子证据的收集难度很大，且海量的电子证据之间的相关性不易分析的问题，对基于FP-Tree的最大频繁模式(FP-Max)挖掘算法的优缺点进行了分析，根据FP-Max算法所存在的缺点并结合实际提出一种通过构建FP矩阵的FP-array的高性能关联规则挖掘算法，并将该算法用于典型的计算机犯罪电子证据的相关性数据挖掘中，可用于成功地挖掘比较常见的五类计算机犯罪数据，挖掘结果可为实际的破案过程提供重要参考。

Computer Crime Data Mining Based on FP-array

Since the electronic evidence is difficult to collect in the computer crime in morden society, a new high-performance algorithm for mining association rules based on the construction of the FP-array is proposed according to the discuss of the maximal frequent patterns (FP-Max) algorithm based on FP-tree. Five kinds of common data of computer-related crime are mined successfully by using the new algorithm. The mining results can provide important reference in actual detection process.