An Overview of Direct Diagnosis and Repair Techniques in the WeeVis Recommendation Environment
arXiv:2102.12327
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