A n incremental updating technique is developed for maintenance of the association rules discovered b y database mining. There have been many studies on eficient discovery of association rules in large databases. However, it is nontrivial t o maintain such discovered rules in large databases because a database may allow frequent or occasional updates and such updates may not only invalidate some existing strong association rules but also turn some weak rules into strong ones. In this study, an incremental updating technique is proposed for eficient maintenance of discovered association rules when new transaction data are added to a transaction database. *The research of the first three authors were supported in part by RGC (the Hong Kong Research Grants Council) grant 338 f O65/OO26. The research of the second author was also supported in part by NSERC (the Natural Sciences and Engineering Research Council of Canada) research grant OGP0037230 and an NCE (the Networks of Centres of Excellence of Canada) research grant, IRIS-HMI5. for all the data. Therefore, the number of rules returned from a mining activity could be large. 3. The rules discovered from a database only reflect the current state of the database. To make the rules discovered stable and reliable, a large volume of data should be collected over a substantial period of time.

Abstract