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.
|Title of host publication||Soft Computing in Industrial Applications|
|Publication status||Published - 2011|
|Name||Advances in Intelligent and Soft Computing|
- Multi-Agent Systems
- Distributed Data Mining
- Association Rules
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