Abstract: For mining causality rules in an event database, the rules are obtained by iteratively generating candidate rules and counting their occurrences in the event database. Newly identified causality rules are used to generate the next set of candidate rules to be evaluated, by increasing the size of the set of consequential events triggered by triggering events and/or the number of triggering events. The preferred embodiment uses an iterative approach to deriving the causality rules in order of the consequential set sizes and triggering set sizes. The detection of an occurrence of a causality rule in an event sequence is handled as a sub-sequence matching problem using a novel hierarchical matching method to improve efficiency.