NDLI: A Fast Algorithm for Mining Closed Itemsets under the Length-Decreasing Support Constraint

Content Provider	IEEE Xplore Digital Library
Author	Liangjun Zang Li Wang
Copyright Year	2006
Description	Author affiliation: Sch. of Comput. Sci. & Eng., Anshan Univ. of Sci. & Technol. (Liangjun Zang; Li Wang)
Abstract	Mining frequent itemsets or patterns is a fundamental and essential problem in many data mining application. Because of the inherent computational complexity, mining the complete set of frequent patterns remains to be a difficult task. Mining closed patterns is a good solution to the problem. And previous study has show that mining frequent patterns with length-decreasing support constraint is very helpful in removing some uninteresting patterns. Therefore, in this paper, we study how to mine closed itemsets under length-decreasing support constraint. We have proposed several new pruning methods to enhance the closed itemset mining under new constraint, and developed an efficient algorithm, LDS_CLOSED. Experimental results show that LDS_CLOSED not only generates more concise result set, but also runs much faster than the existing mining algorithm, DCI_CLOSED
Starting Page	6059
Ending Page	6063
File Size	323296
Page Count	5
File Format	PDF
ISBN	1424403324
DOI	10.1109/WCICA.2006.1714244
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2006-06-21
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Data mining Itemsets Computer science Data engineering Electronic mail Application software Computational complexity Intelligent control Automation length-decreasing support constraint data mining frequent closed itemset
Content Type	Text
Resource Type	Article

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