Building Effective Recommender Systems

Supporting the user with the decision-making and buying process, recommender systems have proven to be a valuable means for online users to cope with the virtual information overload. It is one of the most powerful and popular tools in electronic commerce available today. Development of recommender systems is a multi-disciplinary effort, involving experts from various fields such as data mining, artificial intelligence, statistics, human computer interaction, information retrieval/technology, and adaptive user interfaces. This book covers all aspects and important techniques for recommender systems, such as collaborative filtering, content based techniques, popular hybrid approaches and a detailed tutorial of recommender systems software. Designed for industry researchers in the fields of information technology, e-commerce, information retrieval, data mining, databases and statistics, and practitioners, this book is also suitable for advanced-level students in computer science as a secondary textbook.