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

With the increasing popularity of location-aware social media services, next-Point-of-Interest
(POI) recommendation has gained significant research interest. The key challenge of next …

Subspace learning decreases the dimensions for high-dimensional data by projecting the
original data into a low-dimensional subspace, as well as preserving the similarity among …

Self-supervised representation learning (SSRL) concerns the problem of learning a useful
data representation without the requirement for labelled or annotated data. This …

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 …

As an e-commerce feature, the recommender system can enhance the consumer shopping
experience and create huge benefits for businesses. The e-tourism has become one of the …

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 …

Linked open data is a relatively new topic area with great potential in a wide range of fields.
In the tourism domain, many studies are using linked open data to address the problem of …

With the wide use of Location-Based Social Networks (LBSNs), predicting user friendship
from online social relations and offline trajectory data is of great value to improve the …

With the popularity of smart mobile terminals and advances in wireless communication and
positioning technologies, Geo-Social Networks (GSNs), which combine location awareness …