Mining Association Rules with Item Constraints

The problem of discovering association rules has received considerable research attention and several fast algorithms for mining association rules have been developed. In practice, users are often interested in a subset of association rules. For example, they may only want rules that contain a speci c item or rules that contain children of a speci c item in a hierarchy. While such constraints can be applied as a postprocessing step, integrating them into the mining algorithm can dramatically reduce the execution time. We consider the problem of integrating constraints that are boolean expressions over the presence or absence of items into the association discovery algorithm. We present three integrated algorithms for mining association rules with item constraints and discuss their tradeo s.

• Type: Conference
• Year: 1997
• Where: KDD
• Authors: Ramakrishnan Srikant, Quoc Vu, Rakesh Agrawal
• Keywords: Algorithms, Association Rules, Considerable Research Attention, Data Mining, KDD 1997