An efficient algorithm for mining frequent maximal and closed itemsets

Authors:
Tarek F. Gharib
Affiliations:
Faculty of Computer and Information Sciences, Ain Shams University, Cairo, Egypt. E-mail: tgharib@eun.eg
Venue:
International Journal of Hybrid Intelligent Systems
Year:
2009

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Abstract

The mining of frequent patterns is a basic problem in data mining applications. Frequent maximal and closed itemsets mining has become an important alternative of association rule mining. In this paper we present an effective algorithm which based on the blanket approach for mining all frequent maximal & closed itemsets. The performance of the proposed algorithm had been compared with recently developed algorithms. The results show how the proposed algorithm gives better performance. This is achieved by examining the performance and functionality of the proposed technique.