Paper Info
Title
Distributed BitTable multi-agent association rules mining algorithm
Abstract
Many algorithms have been proposed for the discovery of association rules. The efficiency of these algorithms needs to be improved to handle realworld 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.
Year
Venue
Keywords
2011
KES (1)
bittable multi-agent association rule,algorithms need,apriori-like algorithm,mining algorithm,multi-agent system,new data structure,association rule,underlying data structure,bit vector data structure,better performance,data structure,mas algorithm
Field
DocType
Volume
Data mining,Data structure,Computer science,A priori and a posteriori,Implementation,FSA-Red Algorithm,Multi-agent system,Association rule learning,Distributed algorithm,Artificial intelligence,Bit array,Machine learning
Conference
6881
ISSN
Citations 
PageRank 
0302-9743
0
0.34
References 
Authors
9
3
Name
Order
Citations
PageRank
Walid Adly Atteya140.82
Keshav Dahal218014.11
M. Alamgir Hossain310716.52