Empirical Analysis of Session-Based Recommendation Algorithms

Understand

Recommender systems are tools that support online users by pointing them to potential items of interest in situations of information overload.

• In recent years, the class of session-based recommendation algorithms received more attention in the research literature.
• These algorithms base their recommendations solely on the observed interactions with the user in an ongoing session and do not require the existence of long-term preference profiles.
• Most recently, a number of deep learning based ("neural") approaches to session-based recommendations were proposed.