A survey of erasable itemset mining algorithms

Abstract

Pattern mining, one of the most important problems in data mining, involves finding existing patterns in data. This article provides a survey of the available literature on a variant of pattern mining, namely erasable itemset (EI) mining. EI mining was first presented in 2009 and META is the first algorithm to solve this problem. Since then, a number of algorithms, such as VME, MERIT, and dMERIT+, have been proposed for mining EI. MEI, proposed in 2014, is currently the best algorithm for mining EIs. In this study, the META, VME, MERIT, dMERIT+, and MEI algorithms are described and compared in terms of mining time and memory usage. WIREs Data Mining Knowl Discov 2014, 4:356–379. doi: 10.1002/widm.1137This article is categorized under: Algorithmic Development > Association Rules