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Article type: Research Article
Authors: Li, Yu | Kubat, Miroslav
Affiliations: Department of Electrical and Computer Engineering, University of Miami, 1251 Memorial Drive, Coral Gables, FL 33146, USA. E-mails: yuli74@hotmail.com, mkubat@miami.edu
Abstract: One of the goals of Association Mining is to develop algorithms capable of finding frequently co-occurring groups of items (“itemsets”) in transaction databases. The recently published technique of Itemset Trees expedited the processing of so-called “targeted queries” where the user is interested only in itemsets that contain certain prespecified items. However, the technique did not seem to offer any cost-effective way how to find all frequent itemsets (“general queries”) as it is common with other association-mining algorithms. The purpose of this paper is to rectify this deficiency by a newly developed algorithm that we call IT-Mining. Experimental results indicate that itemset trees can now with advantage be used to answer both targeted and general queries, and that the technique compares favorably with previous atttempts under a broad range of data parameters.
Keywords: Data mining, frequent itemsets, itemset trees
DOI: 10.3233/IDA-2006-10202
Journal: Intelligent Data Analysis, vol. 10, no. 2, pp. 105-120, 2006
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