Exploring temporal effects for location recommendation on location-based social networks
Location-based social networks (LBSNs) have attracted an inordinate number of users and
greatly enriched the urban experience in recent years. The availability of spatial, temporal …
greatly enriched the urban experience in recent years. The availability of spatial, temporal …
iGeoRec: A personalized and efficient geographical location recommendation framework
Geographical influence has been intensively exploited for location recommendations in
location-based social networks (LBSNs) due to the fact that geographical proximity …
location-based social networks (LBSNs) due to the fact that geographical proximity …
Spatiotemporal sequential influence modeling for location recommendations: A gravity-based approach
Recommending to users personalized locations is an important feature of Location-Based
Social Networks (LBSNs), which benefits users who wish to explore new places and …
Social Networks (LBSNs), which benefits users who wish to explore new places and …
Recommendations in location-based social networks: a survey
Recent advances in localization techniques have fundamentally enhanced social
networking services, allowing users to share their locations and location-related contents …
networking services, allowing users to share their locations and location-related contents …
Modeling temporal effects of human mobile behavior on location-based social networks
The rapid growth of location-based social networks (LBSNs) invigorates an increasing
number of LBSN users, providing an unprecedented opportunity to study human mobile …
number of LBSN users, providing an unprecedented opportunity to study human mobile …
TICRec: A probabilistic framework to utilize temporal influence correlations for time-aware location recommendations
In location-based social networks (LBSNs), time significantly affects users' check-in
behaviors, for example, people usually visit different places at different times of weekdays …
behaviors, for example, people usually visit different places at different times of weekdays …
Location recommendation in location-based social networks using user check-in data
This paper studies the problem of recommending new venues to users who participate in
location-based social networks (LBSNs). As an increasingly larger number of users partake …
location-based social networks (LBSNs). As an increasingly larger number of users partake …
Modeling user mobility for location promotion in location-based social networks
With the explosion of smartphones and social network services, location-based social
networks (LBSNs) are increasingly seen as tools for businesses (eg, restaurants, hotels) to …
networks (LBSNs) are increasingly seen as tools for businesses (eg, restaurants, hotels) to …
Location recommendation for out-of-town users in location-based social networks
Most previous research on location recommendation services in location-based social
networks (LBSNs) makes recommendations without considering where the targeted user is …
networks (LBSNs) makes recommendations without considering where the targeted user is …
Context-aware friend recommendation for location based social networks using random walk
The location-based social networks (LBSN) facilitate users to check-in their current location
and share it with other users. The accumulated check-in data can be employed for the …
and share it with other users. The accumulated check-in data can be employed for the …