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Erschienen in:
Recommender Systems: Introduction and Challenges Kapitel lesen Erstes Kapitel lesen

2015 | OriginalPaper | Buchkapitel

25. Multi-Criteria Recommender Systems

verfasst von : Gediminas Adomavicius, YoungOk Kwon

Erschienen in: Recommender Systems Handbook

Verlag: Springer US

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Abstract

This chapter aims to provide an overview of the class of multi-criteria recommender systems, i.e., the category of recommender systems that use multi-criteria preference ratings. Traditionally, the vast majority of recommender systems literature has focused on providing recommendations by modelling a user’s utility (or preference) for an item as a single preference rating. However, where possible, capturing richer user preferences along several dimensions—for example, capturing not only the user’s overall preference for a given movie but also her preferences for specific movie aspects (such as acting, story, or visual effects)—can provide opportunities for further improvements in recommendation quality. As a result, a number of recommendation techniques that attempt to take advantage of such multi-criteria preference information have been developed in recent years. A review of current algorithms that use multi-criteria ratings for calculating predictions and generating recommendations is provided. The chapter concludes with a discussion on open issues and future challenges for the class of multi-criteria rating recommenders.

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Vorheriges Kapitel Active Learning in Recommender Systems
Nächstes Kapitel Novelty and Diversity in Recommender Systems
Fußnoten
1
In some recommender systems, R(u, i) might not contain the overall ratings r 0 in addition to k multi-criteria ratings, i.e., R(u, i) = (r 1, …, r k ). In this case, all the formulas in this subsection will still be applicable with index c ∈ { 1, …, k}, as opposed to c ∈ { 0, 1, …, k}.
 
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Metadaten
Titel
Multi-Criteria Recommender Systems
verfasst von
Gediminas Adomavicius
YoungOk Kwon
Copyright-Jahr
2015
Verlag
Springer US
Buch
Recommender Systems Handbook

Print ISBN: 978-1-4899-7636-9

Electronic ISBN: 978-1-4899-7637-6

Copyright-Jahr: 2015

DOI
https://doi.org/10.1007/978-1-4899-7637-6_25

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