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A configuration-based recommender system for supporting e-commerce decisions

URN to cite this document:
urn:nbn:de:bvb:355-epub-346475
Scholz, Michael ; Dorner, Verena ; Schryen, Guido ; Benlian, Alexander
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Date of publication of this fulltext: 30 Sep 2016 07:42


Abstract

Multi-attribute value theory (MAVT)-based recommender systems have been proposed for dealing with issues of existing recommender systems, such as the cold-start problem and changing preferences. However, as we argue in this paper, existing MAVT-based methods for measuring attribute importance weights do not fit the shopping tasks for which recommender systems are typically used. These methods ...

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