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An Introduction to Recommender Systems Read chapter Read first chapter

2016 | OriginalPaper | Chapter

13. Advanced Topics in Recommender Systems

Author : Charu C. Aggarwal

Published in: Recommender Systems

Publisher: Springer International Publishing

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Abstract

Recommender systems are often used in a number of specialized settings that are not covered in previous chapters of this book. In many cases, the recommendations are performed in settings where there might be multiple users or multiple evaluation criteria. For example, consider a scenario where a group of tourists wish to take a vacation together. Therefore, they may want to obtain recommendations that match the overall interests of the various members in the group. In other scenarios, users may use multiple criteria to provide ratings to items. These variations in the problem formulation can sometimes make the prediction problem more challenging. In particular, we will study the following advanced variations of recommender systems in this chapter:

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previous chapter Attack-Resistant Recommender Systems
Footnotes
1
If the payoffs lie in the range [0, Δ], then the deviation also needs to be scaled up by Δ.
 
2
In traditional recommender systems, items are more likely to have descriptive profiles than users.
 
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Metadata
Title
Advanced Topics in Recommender Systems
Author
Charu C. Aggarwal
Copyright Year
2016
Book
Recommender Systems

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

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

Copyright Year: 2016

DOI
https://doi.org/10.1007/978-3-319-29659-3_13

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