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Mining Closed Itemsets: A Review

Authors: Panida Songram -;

Mining Closed Itemsets: A Review

Abstract

Closed itemset mining is a popular research in data mining. It was proposed to avoid a large number of redundant itemsets in frequent itemset mining. Various algorithms were proposed with efficient strategies to generate closed itemsets. This paper aims to study the existence algorithms used to mine closed itemsets. The various strategies in the algorithms are presented and analyzed in this paper.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
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