Session-aware Recommendation: A Surprising Quest for the State-of-the-art
Sara Latifi,
Noemi Mauro,
Dietmar Jannach
Abstract:Recommender systems are designed to help users in situations of information overload. In recent years, we observed increased interest in session-based recommendation scenarios, where the problem is to make item suggestions to users based only on interactions observed in an ongoing session. However, in cases where interactions from previous user sessions are available, the recommendations can be personalized according to the users' long-term preferences, a process called session-aware recommendation. Today, res… Show more
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