Toward knowledge-driven spiral discovery of exception rules

We report our preliminary endeavour for spiral discovery of exception rules based on discovered pieces of knowledge. An exception rule, which represents a deviational pattern to a general rule, exhibits unexpectedness and is sometimes extremely useful. We have proposed a domain-independent approach for simultaneous discovery of exception rules and their general rules. Exceptions are always interesting to discoverers, as they challenge the existing knowledge and often lead to the growth of knowledge in new directions. We propose a discovery method which exploits pre-discovered pairs of exception rules and their general rules, and apply it to a benchmark data set in knowledge discovery.