A Parallel Computing Model of Agent enabled Mining of Globally Strong Association Rules

International Journal of Artificial Intelligence and Knowledge Discovery

Ram Bahadur Patel³  Gurpreet Singh Bhamra¹  Anil Kumar Verma² 

[1] Maharishi Markandeshwer University. Mulllana, Ambala, Haryana, INDIA;Thapar University,Patiala, Punjab, 147004 – India;Chandigarh College of Engineering & Technology,Chandigarh, 160019- India

关键词: Knowledge Discovery;    Association Rules;    Intelligent Agents;    Multi-Agent System;   

DOI  :  

学科分类：建筑学

来源: RG Education Society

【 摘 要 】

The intelligent agent based model is a popular approach to address scalable mining over large scale  distributed data and is characterized by variety of agents communicating and coordinating with each other to perform the various tasks of data mining (DM) process. Distributed Association Rule Mining (DARM) is the task of generating globally strong association rules from the global frequent itemsets in a distributed environment. In this study a parallel computing model of a multi agent system (MAS) called Agent enabled Mining of Globally Strong Association Rules (AeMGSAR) is presented based on the parallel itinerary of the mobile agents. A running environment is also designed for the implementation and performance study of AeMGSAR system.

【 授权许可】

Unknown