Session-based recommendation (SBR) is a challenging task, which aims at recommending
items based on anonymous behavior sequences. Almost all the existing solutions for SBR …

Session-based recommendation (SBR) has drawn increasingly research attention in recent
years, due to its great practical value by only exploiting the limited user behavior history in …

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 …

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

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 …

Session-based recommendation (SBR), which mainly relies on a user's limited interactions
with items to generate recommendations, is a widely investigated task. Existing methods …

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 the next interaction of a short-term interaction session is a challenging task in
session-based recommendation. Almost all existing works rely on item transition patterns …

The problem of session-based recommendation aims to predict user actions based on
anonymous sessions. Previous methods model a session as a sequence and estimate user …

Session-based recommendation is a challenging task. Without access to a user's historical
user-item interactions, the information available in an ongoing session may be very limited …