Session-based recommendation aims to predict the next item that is most likely to be clicked
by an anonymous user, based on his/her clicking sequence within one visit. It becomes an …

Session-based recommendation nowadays plays a vital role in many websites, which aims
to predict users' actions based on anonymous sessions. There have emerged many studies …

Recent advances in sequence-aware approaches for session-based recommendation, such
as those based on recurrent neural networks, highlight the importance of leveraging …

Session-based recommendation tries to make use of anonymous session data to deliver
high-quality recommendations under the condition that user profiles and the complete …

Given e-commerce scenarios that user profiles are invisible, session-based
recommendation is proposed to generate recommendation results from short sessions …

The problem of session-aware recommendation aims to predict users' next click based on
their current session and historical sessions. Existing session-aware recommendation …

Sequential recommendation aims to leverage users' historical behaviors to predict their next
interaction. Existing works have not yet addressed two main challenges in sequential …

Session-based recommendation (SBR) has received increasing attention to predict the next
item via extracting and integrating both global and local item-item relationships. However …

Predicting a user's preference in a short anonymous interaction session instead of long-term
history is a challenging problem in the real-life session-based recommendation, eg, e …

Different from the traditional recommender system, the session-based recommender system
introduces the concept of the session, ie, a sequence of interactions between a user and …