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

URN to cite this document:: urn:nbn:de:bvb:355-epub-346475
DOI to cite this document:: 10.5283/epub.34647

Scholz, Michael ; Dorner, Verena ; Schryen, Guido ; Benlian, Alexander

Preview

PDF
(317kB)

Date of publication of this fulltext: 30 Sep 2016 07:42

Details

Item type:	Article
Journal or Publication Title:	European Journal of Operational Research
Publisher:	Elsevier
Date:	2017
Institutions:	Business, Economics and Information Systems > Institut für Wirtschaftsinformatik > Alumni or Retired Professors > 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

Preview

Export bibliographical data

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 ...

Owner only: item control page

Download Statistics

More literature (via CORE)

Details

Preview

Export bibliographical data

Abstract

Abstract

Download Statistics

Downloads

More literature (via CORE)

University Library