Recommender systems have significantly developed in recent years in parallel with the
witnessed advancements in both internet of things (IoT) and artificial intelligence (AI) …

Ranking, recommendation, and retrieval systems are widely used in online platforms and
other societal systems, including e-commerce, media-streaming, admissions, gig platforms …

Recommender systems are widely used to provide users with recommendations based on
their preferences. With the ever-growing volume of information online, recommender …

Next Point-of-Interest (POI) recommendation which is of great value to both users and POI
holders is a challenging task since complex sequential patterns and rich contexts are …

Next POI recommendation intends to forecast users' immediate future movements given their
current status and historical information, yielding great values for both users and service …

With the revival of neural networks, many studies try to adapt powerful sequential neural
models, ıe Recurrent Neural Networks (RNN), to sequential recommendation. RNN-based …

“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 …

With the continuous accumulation of users' check‐in data, we can gradually capture users'
behavior patterns and mine users' preferences. Based on this, the next point‐of‐interest …

Crowd flow prediction is of great importance in a wide range of applications from urban
planning, traffic control to public safety. It aims to predict the inflow (the traffic of crowds …

Recommender system is one of the most popular data mining topics that keep drawing
extensive attention from both academia and industry. Among them, POI (point of interest) …