Mining Databases by Means of an Incremental Association Rule Learner

This paper presents an enhanced algorithm for mining incremental updates in large databases. Our paper shows that the algorithm performs significantly faster than the approach of mining the whole updated database from scratch. We first present our enhanced algorithm (PEA), a previously implemented algorithm for mining association rules in large databases. Next, we introduce an incremental algorithm (PIA) for mining incremental updates to a database while efficiently updating the discovered association rules. We present scale up experiments that show how the PIA outperforms the PEA.