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

Scholz, Michael, Dorner, Verena, Schryen, Guido and Benlian, Alexander (2017) A configuration-based recommender system for supporting e-commerce decisions. European Journal of Operational Research. (In Press)

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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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Item type:Article
Date:2017
Institutions:Business, Economics and Information Systems > Institut für Wirtschaftsinformatik > Professur für Wirtschaftsinformatik (Prof. Dr. Guido Schryen)
Keywords:E-Commerce, Recommender System, Attribute Weights, Configuration System, Decision Support
Dewey Decimal Classification:000 Computer science, information & general works > 004 Computer science
Status:In Press
Refereed:Yes, this version has been refereed
Created at the University of Regensburg:Yes
Item ID:34647
Owner only: item control page

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