This book comprehensively covers the topic of recommender systems,
which provide personalized recommendations of items or services to the
new users based on their past behavior. Recommender system methods have
been adapted to diverse applications including social networking, movie
recommendation, query log mining, news recommendations, and computational advertising. This book synthesizes both fundamental and advanced topics of a research area that has now reached maturity. Recommendations
in specific domains and contexts, the context of a recommendation can
be viewed as important side information that affects the recommendation
goals. Different types of context such as temporal data, spatial data, social
data, tagging data, and trustworthiness are explored. In industry point of
view, for an individual item or product recommendation system can help
to developed for better selling.