A Study of Association Rule Mining Algorithms

Abstract

Association rule mining is a technique in data mining for finding frequent patterns, associations, correlations, or causal structures among sets of items or objects in transactional databases, relational databases, and other information repositories.Association rules are created by analysing data for frequent if/then patterns and using the criteria support and confidence to identify the most important relationships. Support is an indication of how frequently the items appear in the database. Confidence indicates the number of times the if/then statements have been found to be true. In this paper, we study different approaches for mining these association rules from relational databases for different areas of application.

Keywords: Data mining, association rules mining, database