An Integrated Knowledge Engineering Environment for Constraint-based Recommender Systems

Constraint-based recommenders support customers in identifying relevant items from complex item assortments. In this paper we present a constraint-based environment already deployed in real-world scenarios that supports knowledge acquisition for recommender applications in a MediaWiki-based context. This technology provides the opportunity do directly integrate informal Wiki content with complementary formalized recommendation knowledge which makes information retrieval for users (readers) easier and less timeconsuming. The user interface supports recommender development on the basis of intelligent debugging and redundancy detection. The results of a user study show the need of automated debugging and redundancy detection even for small-sized knowledge bases.