Các bài báo công bố quốc tế

Tuong Le, Bay Vo; MEI: An efficient algorithm for mining erasable itemsets; Engineering Applications of Artificial Intelligence, Vol. 27 (2014), pp. 155–166 (SCIE).

Abstract

Erasable itemset (EI) mining is an interesting variation of frequent itemset mining which allows managers to carefully consider their production plans to ensure the stability of the factory. Existing algorithms for EI mining require a lot of time and memory. This paper proposes an effective algorithm, called mining erasable itemsets (MEI), which uses the divide-and-conquer strategy and the difference pidset (dPidset) concept for mining EIs fully. Some theorems for efficiently computing itemset information to reduce mining time up and memory usage are also derived. Experimental results show that MEI outperforms existing approaches in terms of both the mining time and memory usage. Moreover, the proposed algorithm is capable of mining EIs with higher thresholds than those obtained using existing approaches.

Keywords

Data mining; Erasable itemset mining; Itemset mining;