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Recommender Systems Handbook

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Cover of 'Recommender Systems Handbook'

Table of Contents

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    Book Overview
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    Chapter 1 Recommender Systems: Introduction and Challenges
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    Chapter 2 A Comprehensive Survey of Neighborhood-Based Recommendation Methods
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    Chapter 3 Advances in Collaborative Filtering
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    Chapter 4 Semantics-Aware Content-Based Recommender Systems
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    Chapter 5 Constraint-Based Recommender Systems
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    Chapter 6 Context-Aware Recommender Systems
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    Chapter 7 Data Mining Methods for Recommender Systems
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    Chapter 8 Evaluating Recommender Systems
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    Chapter 9 Evaluating Recommender Systems with User Experiments
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    Chapter 10 Explaining Recommendations: Design and Evaluation
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    Chapter 11 Recommender Systems in Industry: A Netflix Case Study
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    Chapter 12 Panorama of Recommender Systems to Support Learning
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    Chapter 13 Music Recommender Systems
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    Chapter 14 The Anatomy of Mobile Location-Based Recommender Systems
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    Chapter 15 Social Recommender Systems
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    Chapter 16 People-to-People Reciprocal Recommenders
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    Chapter 17 Collaboration, Reputation and Recommender Systems in Social Web Search
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    Chapter 18 Human Decision Making and Recommender Systems
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    Chapter 19 Privacy Aspects of Recommender Systems
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    Chapter 20 Source Factors in Recommender System Credibility Evaluation
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    Chapter 21 Personality and Recommender Systems
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    Chapter 22 Group Recommender Systems: Aggregation, Satisfaction and Group Attributes
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    Chapter 23 Aggregation Functions for Recommender Systems
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    Chapter 24 Active Learning in Recommender Systems
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    Chapter 25 Multi-Criteria Recommender Systems
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    Chapter 26 Novelty and Diversity in Recommender Systems
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    Chapter 27 Cross-Domain Recommender Systems
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    Chapter 28 Robust Collaborative Recommendation
Attention for Chapter 9: Evaluating Recommender Systems with User Experiments
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Mentioned by

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11 tweeters

Citations

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135 Mendeley
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Chapter title
Evaluating Recommender Systems with User Experiments
Chapter number 9
Book title
Recommender Systems Handbook
Published by
Springer US, January 2015
DOI 10.1007/978-1-4899-7637-6_9
Book ISBNs
978-1-4899-7636-9, 978-1-4899-7637-6
Authors

Bart P. Knijnenburg, Martijn C. Willemsen

Editors

Francesco Ricci, Lior Rokach, Bracha Shapira

Twitter Demographics

The data shown below were collected from the profiles of 11 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 135 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Germany 1 <1%
Netherlands 1 <1%
United Kingdom 1 <1%
Spain 1 <1%
United States 1 <1%
Unknown 130 96%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 41 30%
Student > Master 33 24%
Student > Bachelor 12 9%
Researcher 10 7%
Student > Doctoral Student 7 5%
Other 17 13%
Unknown 15 11%
Readers by discipline Count As %
Computer Science 85 63%
Psychology 9 7%
Social Sciences 6 4%
Business, Management and Accounting 6 4%
Design 4 3%
Other 10 7%
Unknown 15 11%