Because of the widespread adoption of GPS-enabled devices, such as smartphones and
GPS navigation devices, more and more location information is being collected and …

From social media has emerged continuous needs for automatic travel recommendations.
Collaborative filtering (CF) is the most well-known approach. However, existing approaches …

Big data increasingly benefit both research and industrial area such as health care, finance
service and commercial recommendation. This paper presents a personalized travel …

The rapid development of IoT sensors and data provided by Social Networks has
necessitated the fast development of recommender systems as they can be used as a tool to …

The increasing number of users participating in location-based social networks has resulted
in an information overload problem. Recommendation is a process that can free users from …

Trip is an important part of people's lives. We need to obtain interesting location information
quickly and conveniently from the huge amount of information. The existing data source of …

In event-based social networks, user preferences mined from the influences of geographical
locations, event categories, and social and temporal preferences have been exploited for …

With the popularization of internet, event-based social networks (EBSNs) have experienced
recognition among people for planning and communicating social events. Due to plethora of …

Location-based services (LBSs) are becoming an increasingly important component in our
social and business life. All existing LBS providers support the nearest place searching via a …

In event-based social networks, an event recommender helps users to discover events that
align with their preferences from a large number of upcoming events. In this paper, we …