Interestingness, peculiarity, and multi-database mining
Ning Zhong, Muneaki Ohshima, Yiyu Y. Yao, S. Ohsuga · 2002
In order to discover new, surprising, interesting patterns hidden in data, peculiarity oriented mining and multidatabase mining are required. In the paper, we introduce peculiarity rules as a new class of rules, which can be discovered from a relatively low number of peculiar data by searching the relevance among the peculiar data. We give a formal interpretation and comparison of three classes of rules: association rules, exception rules, and peculiarity rules, as well as describe how to mine more interesting peculiarity rules in multiple databases.