Mining association rules from stars

Association rule mining is an important data mining problem. It is found to be useful for conventional relational data. However, previous work has mostly targeted on mining a single table. In real life, a database is typically made up of multiple tables and one important case is where some of the tables form a star schema. The tables typically correspond to entity sets and joining the tables in a star schema gives relationships among entity sets which can be very interesting information. Hence mining on the join result is an important problem. Based on characteristics of the star schema we propose an efficient algorithm for mining association rules on the join result but without actually performing the join operation. We show that this approach can significantly out-perform the join-then-mine approach even when the latter adopts a fastest known mining algorithm.