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