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

2021-02-24 15:02:50
Alexander Felfernig, Stefan Reiterer, Martin Stettinger, Michael Jeran
arXiv_AI
     
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.

Abstract (translated)

URL

https://arxiv.org/abs/2102.12327

PDF

https://arxiv.org/pdf/2102.12327.pdf

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