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

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

doi:10.1007/978-3-540-30132-5_29

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 proceeding › Chapter

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 language	English
Title of host publication	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Editors	Mircea Gh. Negoita, Robert J. Howlett, Lakhmi C. Jain
Publisher	Springer Verlag
Pages	178-188
Number of pages	11
ISBN (Print)	9783540301325
DOIs	https://doi.org/10.1007/978-3-540-30132-5_29
Publication status	Published - Jan 1 2004
Externally published	Yes

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	3213
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

ASJC Scopus subject areas

Theoretical Computer Science
Computer Science(all)

Access to Document

10.1007/978-3-540-30132-5_29

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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

A Peer-to-Peer Approach to Parallel Association Rule Mining. / Ishikawa, Hiroshi; Shioya, Yasuo; Omi, Takeshi; Ohta, Manabu; Katayama, Kaoru.

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). ed. / Mircea Gh. Negoita; Robert J. Howlett; Lakhmi C. Jain. Springer Verlag, 2004. p. 178-188 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 3213).

Research output: Chapter in Book/Report/Conference proceeding › Chapter

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

Ishikawa H, Shioya Y, Omi T, Ohta M, Katayama K. A Peer-to-Peer Approach to Parallel Association Rule Mining. In Negoita MG, Howlett RJ, Jain LC, editors, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Springer Verlag. 2004. p. 178-188. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). https://doi.org/10.1007/978-3-540-30132-5_29

Ishikawa, Hiroshi ; Shioya, Yasuo ; Omi, Takeshi ; Ohta, Manabu ; Katayama, Kaoru. / A Peer-to-Peer Approach to Parallel Association Rule Mining. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). editor / Mircea Gh. Negoita ; Robert J. Howlett ; Lakhmi C. Jain. Springer Verlag, 2004. pp. 178-188 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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