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MaxDomino: Efficiently mining maximal sets

  • Krishnamoorthy Srikumar
  • , Bharat Bhasker
  • , Satish K. Tripathi
  • Indian Institute of Management Lucknow

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

1 Scopus citations

Abstract

We present MaxDomino, an algorithm for mining maximal frequent sets using a novel concept of dominancy factor of a transaction. We also propose a hashing scheme to collapse the database to a form that contains only unique transactions. Unlike traditional bottom up approach with look-aheads, MaxDomino employs a top down strategy with selective bottom up search for mining maximal sets. Using the connect dataset [Benchmark dataset created by University California, Irvine], our experimental results reveal that MaxDomino outperforms GenMax at higher support levels. Furthermore, our scalability tests show that MaxDomino yields an order of magnitude improvement in speed over GenMax. MaxDomino is especially efficient when the maximal frequent sets are longer.

Original languageEnglish
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
EditorsAnne James, Muhammad Younas, Brian Lings
PublisherSpringer Verlag
Pages131-139
Number of pages9
ISBN (Print)3540405364, 9783540405368
DOIs
StatePublished - 2003

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume2712
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

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