Preface Recommender Systems are software tools and techniques providing suggestions for items to be of use to a user. The suggestions provided are aimed at supporting their users in various decision-making processes, such as what items to buy, what music to listen, or what news to read. Recommender systems have proven to be valu able means for online users to cope with the information overload and have become one of the most powerful and popular tools in electronic commerce Correspondingly, various techniques for recommendation generation have been proposed and during the last decade, many of them have also been successfully deployed in commercial environments Development of recommender systems is a multi-disciplinary effort which in- volves experts from various fields such as Artificial intelligence, Human Computer Interaction, Information Technology, Data Mining, Statistics, Adaptive User Inter aces, Decision Support Systems, Marketing, or Consumer Behavior. Recommender Systems Handbook: A Complete Guide for Research Scientists and Practitioners aims to impose a degree of order upon this diversity by presenting a coherent and unified repository of recommender systems' major concepts, theories, methodolo- gies, trends, challenges and applications. This is the first comprehensive book which is dedicated entirely to the field of recommender systems and covers several aspects of the major techniques. Its informative, factual pages will provide researchers, stu- dents and practitioners in industry with a comprehensive, yet concise and con- venient reference source to recommender systems. The book describes in detail the classical methods, as well as extensions and novel approaches that were recently in- troduced. The book consists of five parts: techniques, applications and evaluation of recommender systems, interacting with recommender systems, recommender sys- tems and communities, and advanced algorithms. The first part presents the most popular and fundamental techniques used nowadays for building recommender sys- tems, such as collaborative filtering, content-based filtering, data mining methods and context-aware methods. The second part starts by surveying techniques and ap proaches that have been used to evaluate the quality of the recommendations. Then deals with the practical aspects of designing recommender systems, it describes de- sign and implementation consideration, setting guidelines for the selection of thePreface Recommender Systems are software tools and techniques providing suggestions for items to be of use to a user. The suggestions provided are aimed at supporting their users in various decision-making processes, such as what items to buy, what music Development of recommender systems is a multi-disciplinary effort which in￾volves experts from various fields such as Artificial intelligence, Human Computer Interaction, Information Technology, Data Mining, Statistics, Adaptive User Inter￾faces, Decision Support Systems, Marketing, or Consumer Behavior. Recommender Systems Handbook: A Complete Guide for Research Scientists and Practitioners aims to impose a degree of order upon this diversity by presenting a coherent and unified repository of recommender systems’ major concepts, theories, methodolo￾gies, trends, challenges and applications. This is the first comprehensive book which is dedicated entirely to the field of recommender systems and covers several aspects of the major techniques. Its informative, factual pages will provide researchers, stu￾classical methods, as well as extensions and novel approaches that were recently in￾troduced. The book consists of five parts: techniques, applications and evaluation of recommender systems, interacting with recommender systems, recommender sys￾tems and communities, and advanced algorithms. The first part presents the most popular and fundamental techniques used nowadays for building recommender sys￾tems, such as collaborative filtering, content-based filtering, data mining methods and context-aware methods. The second part starts by surveying techniques and ap￾proaches that have been used to evaluate the quality of the recommendations. Then deals with the practical aspects of designing recommender systems, it describes de￾sign and implementation consideration, setting guidelines for the selection of the vii to listen, or what news to read. Recommender systems have proven to be valu￾able means for online users to cope with the information overload and have Correspondingly, various techniques for recommendation generation have been proposed and during the last decade, many of them have also been successfully deployed in commercial environments. become one of the most powerful and popular tools in electronic commerce. dents and practitioners in industry with a comprehensive, yet concise and con￾venient reference source to recommender systems. The book describes in detail the