Generating (Fuzzy) frequent itemsets by a bitmap-based algorithm-The word's most compact frequent itemset miner

Research output: Contribution to conferencePaper

1 Citation (Scopus)

Abstract

Mining frequent itemsets in databases is an important and widely studied problem in data mining research. The problem of mining frequent itemsets is usually solved by constructing candidates of itemsets, and identifying those itemsets that meet the requirement of frequent itemsets. This paper proposes a novel algorithm based on BitTable (or bitmap) representation of the data. Data-related to frequent itemsets-are stored in spare matrices. Simple matrix and vector multiplications are used to calculate the support of the potential n+1 itemsets. The main benefit of this approach is that only bitmaps of the frequent itemsets are generated. The concept is simple and easily interpretable and it supports a compact and effective implementation (in MATLAB). An application example related to the BMS-WebView-1 benchmark data is presented to illustrate the applicability of the proposed algorithm.

Original languageEnglish
Pages469-479
Number of pages11
Publication statusPublished - Dec 1 2009
Event10th International Symposium of Hungarian Researchers on Computational Intelligence and Informatics, CINTI 2009 - Budapest, Hungary
Duration: Nov 12 2009Nov 14 2009

Other

Other10th International Symposium of Hungarian Researchers on Computational Intelligence and Informatics, CINTI 2009
CountryHungary
CityBudapest
Period11/12/0911/14/09

Keywords

  • BitTable
  • Frequent itemsets

ASJC Scopus subject areas

  • Artificial Intelligence
  • Information Systems

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  • Cite this

    Abonyi, J. (2009). Generating (Fuzzy) frequent itemsets by a bitmap-based algorithm-The word's most compact frequent itemset miner. 469-479. Paper presented at 10th International Symposium of Hungarian Researchers on Computational Intelligence and Informatics, CINTI 2009, Budapest, Hungary.