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Abstract:Constraint-based recommenders support users in the identification of items (products) fitting their wishes and needs. Example domains are financial services and electronic equipment. In this paper we show how divide-and-conquer based (direct) diagnosis algorithms (no conflict detection is needed) can be exploited in constraint-based recommendation scenarios. In this context, we provide an overview of the MediaWiki-based recommendation environment WeeVis.
* A. Felfernig, S. Reiterer, M. Stettinger, and M. Jeran. An Overview
of Direct Diagnosis and Repair Techniques in the WeeVis Recommendation
Environment. In the 25th International Workshop on Principles of Diagnosis,
Graz, Austria, 2014