Recommender Systems Handbook
This second edition of a well-received text, with 20 new chapters, presents a coherent and unified repository of recommender systems’ major concepts, theories, methodologies, trends, and challenges. A variety of real-world applications and detailed case studies are included. In addition to wholesale...
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| Other Authors: | , , |
| Format: | Electronic eBook |
| Language: | English |
| Published: |
New York, NY :
Springer US : Imprint: Springer,
2015.
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| Edition: | 2nd ed. 2015. |
| Subjects: | |
| Online Access: | https://doi.org/10.1007/978-1-4899-7637-6 |
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Table of Contents:
- Recommender Systems: Introduction and Challenges
- A Comprehensive Survey of Neighborhood-based Recommendation Methods
- Advances in Collaborative Filtering
- Semantics-aware Content-based Recommender Systems
- Constraint-based Recommender Systems
- Context-Aware Recommender Systems
- Data Mining Methods for Recommender Systems
- Evaluating Recommender Systems
- Evaluating Recommender Systems with User Experiments
- Explaining Recommendations: Design and Evaluation
- Recommender Systems in Industry: A Netflix Case Study
- Panorama of Recommender Systems to Support Learning
- Music Recommender Systems
- The Anatomy of Mobile Location-Based Recommender Systems
- Social Recommender Systems
- People-to-People Reciprocal Recommenders
- Collaboration, Reputation and Recommender Systems in Social Web Search
- Human Decision Making and Recommender Systems
- Privacy Aspects of Recommender Systems
- Source Factors in Recommender System Credibility Evaluation
- Personality and Recommender Systems
- Group Recommender Systems: Aggregation, Satisfaction and Group Attributes
- Aggregation Functions for Recommender Systems
- Active Learning in Recommender Systems
- Multi-Criteria Recommender Systems
- Novelty and Diversity in Recommender Systems
- Cross-domain Recommender Systems
- Robust Collaborative Recommendation.