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This book introduces different approaches to developing recommender systems that automate choice-making strategies to provide affordable, personal, and high-quality recommendations.
'Behind the modest title of 'An Introduction' lies the type of work the field needs to consolidate its learning and move forward to address new challenges. Across the chapters that follow lie both a tour of what the field knows well - a diverse collection of algorithms and approaches to recommendation - and a snapshot of where the field is today as new approaches derived from social computing and the semantic web find their place in the recommender systems toolbox. Let's all hope this worthy effort spurs yet more creativity and innovation to help recommender systems move forward to new heights.' Joseph A. Konstan, from the Foreword
1. Introduction; Part I. Introduction into Basic Concepts: 2. Collaborative recommendation; 3. Content-based recommendation; 4. Knowledge-based recommendation; 5. Hybrid recommendation approaches; 6. Explanations in recommender systems; 7. Evaluating recommender systems; 8. Case study - personalized game recommendations on the mobile Internet; Part II. Recent Developments: 9. Attacks on collaborative recommender systems; 10. Online consumer decision making; 11. Recommender systems and the next-generation Web; 12. Recommendations in ubiquitous environments; 13. Summary and outlook.