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State of the Art of Reputation-Enhanced Recommender Systems

Richthammer, Christian, Weber, Michael and Pernul, Günther (2018) State of the Art of Reputation-Enhanced Recommender Systems. Web Intelligence 16 (4), pp. 273-286.

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Date of publication of this fulltext: 08 Nov 2018 10:17

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Other URL: https://content.iospress.com/articles/web-intelligence/web394


Abstract

Recommender systems are pivotal components of modern Internet platforms and constitute a well-established research field. By now, research has resulted in highly sophisticated recommender algorithms whose further optimization often yields only marginal improvements. This paper goes beyond the commonly dominating focus on optimizing algorithms and instead follows the idea of enhancing recommender ...

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Item type:Article
Date:31 October 2018
Institutions:Business, Economics and Information Systems > Institut für Wirtschaftsinformatik > Lehrstuhl für Wirtschaftsinformatik I - Informationssysteme (Prof. Dr. Günther Pernul)
Projects:FORSEC
Identification Number:
ValueType
10.3233/WEB-180394DOI
Keywords:Recommender systems, Decision support systems, Reputation, Trust, Reputation-enhanced recommender systems
Dewey Decimal Classification:000 Computer science, information & general works > 004 Computer science
Status:Published
Refereed:Yes, this version has been refereed
Created at the University of Regensburg:Yes
Item ID:37937
Owner only: item control page

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