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

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

Research output: Contribution to journalArticle

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
Pages (from-to)178-188
Number of pages11
JournalLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume3213
Publication statusPublished - 2004
Externally publishedYes

Fingerprint

Association Rule Mining
Association rules
Peer to Peer
P2P Network
Load Balancing
Resource allocation
Peer to peer networks
Peer-to-peer Networks
Distributed computer systems
Association Rules
Vertex of a graph
Distributed Computing
Network Topology
Partitioning
Topology
Technology
Internal
Costs and Cost Analysis
Evaluate
Evaluation

ASJC Scopus subject areas

  • Computer Science(all)
  • Biochemistry, Genetics and Molecular Biology(all)
  • Theoretical Computer Science

Cite this

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

In: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Vol. 3213, 2004, p. 178-188.

Research output: Contribution to journalArticle

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