ABSTRACT
Recommendation systems are important applications that are essential for numerous business models. Recommendation systems suggest appropriate items based on user preference and historical purchase data. These systems are based on the principle that if users shared the same interests in the past, they will, with high probability, exhibit similar behavior in the future. The historical data that refl ect user preference may comprise explicit ratings,Web click logs, or tags. Personalization is evidently an important factor in an effective recommendation system. In this chapter, we will introduce the basic concepts and main strategies for recommendation systems.
