This article studies the problem of learning effective representations for Location-Based
Social Networks (LBSN), which is useful in many tasks such as location recommendation …

Learning latent representations for users and points of interests (POIs) is an important task in
location-based social networks (LBSN), which could largely benefit multiple location-based …

Location-based social networks (LBSNs) have emerged over the past few years. Their
exponential network effects depend on the fact that each user can share her daily digital …

Location-based embedding is a fundamental problem to solve in location-based social
networks (LBSN). In this paper, we propose a geographical convolutional neural tensor …

In this article, we investigate the problem of social link inference in a target location-aware
social network (LSN), which aims at predicting the unobserved links between users within …

Friend recommendation from user trajectory is a vital real-world application of location-
based social networks (LBSN) services. Previous statistical analysis indicated that social …

The wide spread of location-based social networks brings about a huge volume of user
check-in data, which facilitates the recommendation of points of interest (POIs). Recent …

Many social network applications depend on robust representations of spatio-temporal data.
In this work, we present an embedding model based on feed-forward neural networks which …

Location-Based Social Networks (LBSNs) have been widely used as a primary data source
for studying the impact of mobility and social relationships on each other. Traditional …

Current link prediction methods in Location-Based Social Networks (LBSNs) fuse graphs
derived from users' check-in data and their social links to form a single graph or network …