精简高效用模式挖掘综述

Survey of algorithms for concise high utility pattern mining

全集高效用模式挖掘算法存在的关键问题之一是会产生冗余的高效用项集,这将导致用户很难在大量的高效用项集中发现有用的信息,严重降低了高效用模式挖掘算法的性能。为解决这一问题,衍生出了精简高效用模式挖掘算法,其主要包括最大高效用模式、闭合高效用模式、top-k高效用模式以及三者之间的组合高效用模式挖掘算法等。首先,介绍了精简高效用模式的相关问题描述;然后,从有无候选项集生成、一两阶段挖掘方法、数据结构类型和剪枝策略等角度,重点分类总结了精简高效用模式挖掘方法;最后,给出了精简高效用模式的进一步研究方向,包括处理基于负项的高效用精简模式、处理基于时间的高效用精简模式及处理动态复杂的数据等。

There is a key problem in the complete set high utility pattern mining algorithms,which is that there are too many redundant high utility itemsets.This makes it difficult for users to find useful information in a large set of high utility itemsets,which seriously reduces the performance of high utility pattern mining algorithms.To solve this problem,it derived a concise high utility pattern mining method,which mainly included the maximal high utility pattern,the closed high utility pattern,the top-k high utility pattern,and the combination high utility pattern mining method among the three.First,this paper introduced the related problem descriptions of concise high utility patterns.Then,from the perspectives of candidate set generation,data structure types,and pruning strategies,the paper summarized concise high utility pattern mining methods.Finally,this paper gave further research directions for concise high utility pattern,including the processing of concise high utility pattern based on negative terms,concise high utility pattern based on time and deal with dynamic and complex data.