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Erschienen in:
An Introduction to Recommender Systems Kapitel lesen Erstes Kapitel lesen

2016 | OriginalPaper | Buchkapitel

7. Evaluating Recommender Systems

verfasst von : Charu C. Aggarwal

Erschienen in: Recommender Systems

Verlag: Springer International Publishing

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Abstract

The evaluation of collaborative filtering shares a number of similarities with that of classification. This similarity is due to the fact that collaborative filtering can be viewed as a generalization of the classification and regression modeling problem (cf. section 1.​3.​1.​3 of Chapter 1).

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Vorheriges Kapitel Ensemble-Based and Hybrid Recommender Systems
Nächstes Kapitel Context-Sensitive Recommender Systems
Fußnoten
1
The actual design in methods such as cross-validation is slightly more complex because the data are segmented in multiple ways, even though they are always divided into two parts during a particular execution phase of training.
 
2
A related effect is that observed ratings are likely to be specified by users who are frequent raters. Frequent raters may show different patterns of rating values compared to infrequent raters.
 
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Metadaten
Titel
Evaluating Recommender Systems
verfasst von
Charu C. Aggarwal
Copyright-Jahr
2016
Buch
Recommender Systems

Print ISBN: 978-3-319-29657-9

Electronic ISBN: 978-3-319-29659-3

Copyright-Jahr: 2016

DOI
https://doi.org/10.1007/978-3-319-29659-3_7