Searching for high-support itemsets in itemset trees

Research output: Contribution to journalArticle

9 Citations (Scopus)

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.

Original languageEnglish
Pages (from-to)105-120
Number of pages16
JournalIntelligent Data Analysis
Volume10
Issue number2
StatePublished - Dec 1 2006

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Mining
Query
Frequent Itemsets
Transactions
Costs
Experimental Results
Processing
Range of data

Keywords

  • Data mining
  • frequent itemsets
  • itemset trees

ASJC Scopus subject areas

  • Artificial Intelligence
  • Theoretical Computer Science
  • Computer Vision and Pattern Recognition

Cite this

Searching for high-support itemsets in itemset trees. / Li, Yu; Kubat, Miroslav.

In: Intelligent Data Analysis, Vol. 10, No. 2, 01.12.2006, p. 105-120.

Research output: Contribution to journalArticle

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