The rapid development of cities has led to increasingly problems in the road network
structure of urban streets. Combining emerging big data technology with traditional street …

Numbers of sharing economy services are significantly increasing recently. Using
computational techniques to obtain customer's behavior on these services are very helpful to …

With the popularity of mobile devices and smartphones, we have witnessed rapid growth in
mobile applications and services, especially in location-based services (LBS). According to …

While collaborative filtering (CF) is the most popular approach for recommendation systems,
it only makes use of the ratings given to items by users and neglects side information about …

The availability of charging stations is an important factor for promoting electric vehicles
(EVs) as a carbon-friendly way of transportation. Hence, for city planners, the crucial …

Location-based social networks (LBSNs), such as Foursquare, fostered the emergence of
new tasks such as recommending venues a user might wish to visit. In the literature …

Twitter has attracted billions of users for life logging and sharing activities and opinions. In
their tweets, users often reveal their location information and short‐term visiting histories or …

Abstract Points of Interest (POIs) are crucial data sources for location based applications.
Social media and traditional web can include up-to-date POI information that is emerging in …

The task of POI attribute acquisition, which aims at completing missing attributes (eg, POI
name, address, status, phone, and open/close time) for a point of interest (POI) or updating …

This paper shows the usefulness of open source points-of-interest (POI) data for
understanding the causes of volatility in residential property prices. Points of interest are …