Recommender systems are one of the most successful applications of data mining and
machine-learning technology in practice. Academic research in the field is historically often …

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

“Nature shows us only the tail of the lion. But I do not doubt that the lion belongs to it even
though he cannot at once reveal himself because of his enormous size.”–Albert Einstein The …

Predicting personalized sequential behavior is a key task for recommender systems. In order
to predict user actions such as the next product to purchase, movie to watch, or place to visit …

Deep learning methods have led to substantial progress in various application fields of AI,
and in recent years a number of proposals were made to improve recommender systems …

Recommender systems help users find relevant items of interest, for example on e-
commerce or media streaming sites. Most academic research is concerned with approaches …

Recurrent neural networks for session-based recommendation have attracted a lot of
attention recently because of their promising performance. repeat consumption is a common …

Commercial e-learning platforms have to overcome the challenge of resource overload and
find the most suitable material for educators using a recommendation system (RS) when an …

Next basket recommendation is a crucial task in market basket analysis. Given a user's
purchase history, usually a sequence of transaction data, one attempts to build a …

Recommender systems are software applications that make tailored item suggestions to
users, usually with the goal of hel** them overcome information overload or make …