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Statistical Methods for Recommender Systems

Author: Deepak K Agarwal; Bee-Chung Chen
Publisher: Cambridge : Cambridge University Press, 2016.
Edition/Format:   eBook : Document : EnglishView all editions and formats
Summary:
Designing algorithms to recommend items such as news articles and movies to users is a challenging task in numerous web applications. The crux of the problem is to rank items based on users' responses to different items to optimize for multiple objectives. Major technical challenges are high dimensional prediction with sparse data and constructing high dimensional sequential designs to collect data for user modeling  Read more...
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Genre/Form: Electronic books
Additional Physical Format: Print version:
Agarwal, Deepak.
Statistical methods for recommender systems.
[Place of publication not identified] : Cambridge Univ Press, 2015
(OCoLC)928442647
Material Type: Document, Internet resource
Document Type: Internet Resource, Computer File
All Authors / Contributors: Deepak K Agarwal; Bee-Chung Chen
ISBN: 9781139565868 1139565869
OCLC Number: 938434960
Notes: Title from publisher's bibliographic system (viewed on 09 Feb 2016).
Description: 1 online resource
Contents: Part I. Introduction: 1. Introduction; 2. Classical methods; 3. Explore/exploit for recommender problems; 4. Evaluation methods; Part II. Common Problem Settings: 5. Problem settings and system architecture; 6. Most-popular recommendation; 7. Personalization through feature-based regression; 8. Personalization through factor models; Part III. Advanced Topics: 9. Factorization through latent dirichlet allocation; 10. Context-dependent recommendation; 11. Multi-objective optimization.
Responsibility: Deepak K. Agarwal, Bee-Chung Chen.

Abstract:

This book provides an in-depth discussion of challenges encountered in deploying real-life large-scale systems and the state-of-the-art solutions in personalization.  Read more...

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'This book provides a comprehensive guide to state-of-the-art statistical techniques that are used to power recommender systems. ... The text is authoritative and well written, with the authors Read more...

 
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