A Peer-to-Peer Approach to Parallel Association Rule Mining

Hiroshi Ishikawa, Yasuo Shioya, Takeshi Omi, Manabu Ohta, Kaoru Katayama

Research output: Chapter in Book/Report/Conference proceedingChapter

2 Citations (Scopus)

Abstract

Distributed computing based on P2P (peer-to-peer) networks is a technology attainable at a relatively low cost. This enables us to propose a flexible approach based on "Parution" algorithm as an extension of "Aprion"' algorithm to efficiently mine association rules by cooperatively partitioning and distributing processes to nodes on a virtually tree-like P2P network topology. The concept of cooperation here means that any internal node contributes to the control of the whole processes. First, we describe the general design of our basic approach and compare it with related techniques. We explain the basic algorithm (without load balancing) implemented as experimental programs in detail. Next, we explain simulation settings and discuss evaluation results, which can validate the effectiveness of our basic approach. Further, we describe and evaluate the algorithm with load balancing as an extension to the basic algorithm.

Original languageEnglish
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
EditorsMircea Gh. Negoita, Robert J. Howlett, Lakhmi C. Jain
PublisherSpringer Verlag
Pages178-188
Number of pages11
ISBN (Print)9783540301325
DOIs
Publication statusPublished - Jan 1 2004
Externally publishedYes

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume3213
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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  • Cite this

    Ishikawa, H., Shioya, Y., Omi, T., Ohta, M., & Katayama, K. (2004). A Peer-to-Peer Approach to Parallel Association Rule Mining. In M. G. Negoita, R. J. Howlett, & L. C. Jain (Eds.), Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (pp. 178-188). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 3213). Springer Verlag. https://doi.org/10.1007/978-3-540-30132-5_29