Recently, recommender systems have played an increasingly important role in a wide
variety of commercial applications to help users find favourite products. Research in the …

Recommender systems have recently been singled out as a fascinating area of research,
owing to the technological progress in mobile devices, such as smartphones and tablets, as …

Spatial keyword search has been playing an indispensable role in personalized route
recommendation and geo-textual information retrieval. In this light, we conduct a survey on …

Recently, explainable recommendation has attracted increasing attentions, which can make
the recommender system more transparent and improve user satisfactions by …

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 development of location-based services (LBS), many location-based social sites
like Foursquare and Plancast have emerged. People can organize and participate in group …

Matrix factorization is one of the most popular methods in recommendation systems.
However, it faces two challenges related to the check-in data in point of interest (POI) …

The emergence of Location-based social networks (LBSNs) in recent years has boosted
improvements in Recommender Systems for a new and specific task: the recommendation of …

The popularization of Location-based social networks (LBSNs) in last years has provided a
lot of improvements in several Recommender Systems to the task of points-of-interest (POI) …

Recommender systems have been an important tool to filter and tailor the best content for
online users. Classical recommender system methods typically face the filter bubble …