Decentralized Association Rule Mining on Web Using Rough Set Theory

Decentralized Association Rule Mining on Web Using Rough Set Theory

A central part of many algorithms for mining association rules in large data sets is a procedure that is to find so called frequent itemsets. The frequent itemsets are very large due to transactions data increasing. This paper proposes a new approach to find frequent itemsets employing rough set theory that can extract association rules for each homogenou.s cluster of transaction data records and relationships between different clusters. This paper conducts an algorithm to reduce a large number of itemsets to find valid association rules.