Incrememtal Maintenance of Ontology-Exploiting Association Rules

The problem of mining association rules incorporated with domain knowledge (ontology) has attracted lots of researchers´ attention recently. In our previous work, we have considered and devised two efficient algorithms, called AROC and AROS, for mining association rules with ontological information that presents not only classification but also composition relationship. In this paper, we continue this study toward the maintenance issue: how to efficiently maintaining the discovered ontology-incorporated association rules as frequent update happens to the data sources. An effective algorithm is proposed. Empirical evaluation showed that the proposed algorithm is significantly more efficient than running AROC or AROS on the updated database afresh.