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MaxDomino: Efficiently Mining Maximal Sets

  • Krishnamoorthy Srikumar
  • Bharat Bhasker
  • Satish K. Tripathi
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2712)

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.

Keywords

Association Rule Dominancy Factor Hash Table Candidate Subset Hash Tree 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2003

Authors and Affiliations

  • Krishnamoorthy Srikumar
    • 1
  • Bharat Bhasker
    • 1
  • Satish K. Tripathi
    • 1
  1. 1.Indian Institute of ManagementLucknowIndia

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