Introspective Subgroup Analysis for Interactive Knowledge Refinement.
Martin Atzmüller, Joachim Baumeister, Frank Puppe · 2006
When knowledge systems are deployed into a real-world ap-plication, then the maintenance and the refinement of the knowledge are essential tasks. Many existing automatic knowledge refinement methods only provide limited control and clarification capabilities during the refinement process. Furthermore, often assumptions about the correctness of the knowledge base and the cases are made. However, such as-sumptions do not necessarily hold for real-world applications. In this paper, we present a novel interactive approach for the refinement of knowledge bases: Subgroup mining is used to discover local patterns that describe factors potentially caus-ing incorrect behavior of the knowledge system. The ap-proach is supplemented by introspective subgroup analysis techniques in order to help the user with the interpretation of the refinement recommendations proposed by the system.