Multi-Agent Association Rules Mining in Distributed Databases

Walid Adly Atteya, Keshav Dahal, M. Alamgir Hossain

Research output: Chapter in Book/Report/Conference proceedingChapter

2 Citations (Scopus)

Abstract

In this paper, we present a collaborative multi-agent based system for mining association rules from distributed databases. The proposed model is based on cooperative agents and is compliant to the Foundation for Intelligent Physical Agents standard. This model combines different types of technologies, namely the association rules as a data mining technique and the multi-agent systems to build a model that can operate on distributed databases rather than working on a centralized database only. The autonomous and the social abilities of the model agents provided the ability to operate cooperatively with each other and with other different external agents, thus offering a generic platform and a basic infrastructure that can deal with other data mining techniques. The platform has been compared with the traditional association rules algorithms and has proved to be more efficient and more scalable.
Original languageEnglish
Title of host publicationSoft Computing in Industrial Applications
Pages305-314
Volume96
DOIs
Publication statusPublished - 2011
Externally publishedYes

Publication series

NameAdvances in Intelligent and Soft Computing

Keywords

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

Cite this

Atteya, W. A., Dahal, K., & Hossain, M. A. (2011). Multi-Agent Association Rules Mining in Distributed Databases. In Soft Computing in Industrial Applications (Vol. 96, pp. 305-314). (Advances in Intelligent and Soft Computing). https://doi.org/10.1007/978-3-642-20505-7_27