Distributed BitTable Multi-Agent Association Rules Mining Algorithm

Walid Adly Atteya, Keshav Dahal, M. Alamgir Hossain

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


Many algorithms have been proposed for the discovery of association rules. The efficiency of these algorithms needs to be improved to handle real-world large datasets. This efficiency can be determined mainly by three factors. The way candidates are generated, the way their supports are counted and the data structure used. Most papers focus on the first and the second factors while few focus on the underlying data structures. In this paper, we present a distributed Multi-Agent based algorithm for mining association rules in distributed environments. The distributed MAS algorithm uses Bit vector data structure that was proved to have better performance in centralized environments. The algorithm is implemented in the context of Multi-Agent systems and complies with global communication standard Foundation for Intelligent Physical Agents (FIPA). The distributed Multi-Agent based algorithm with its new data structure improves implementations reported in the literature that were based on Apriori. The algorithm has better performance over Apriori-like algorithms.
Original languageEnglish
Title of host publicationKnowledge-based and Intelligent Information and Engineering Systems, Pt 1
ISBN (Print)978-3-642-23850-5
Publication statusPublished - 2011
Externally publishedYes

Publication series

NameLecture Notes in Computer Science


  • Multi-Agent Systems
  • Distributed Data Mining
  • Association Rules


Dive into the research topics of 'Distributed BitTable Multi-Agent Association Rules Mining Algorithm'. Together they form a unique fingerprint.

Cite this