Recommender systems are widely adopted as an increasing research and development
area, since they provide users with diverse and useful information tailored to their needs …

Nowadays, large-scale individual trajectories can be collected by various location-based
social network services, which enables us to better understand human mobility patterns …

Trajectory-User Linking (TUL) is crucial for human mobility modeling by linking different
trajectories to users with the exploration of complex mobility patterns. Existing works mainly …

Trajectory-User Linking (TUL) is a relatively new mobility classification task in which
anonymous trajectories are linked to the users who generated them. With applications …

Characterizing human driver's driving behaviors from global positioning system (GPS)
trajectories is an important yet challenging trajectory mining task. Previous works heavily …

Trajectories, a specific type of mobility data, can be used for many useful data mining tasks.
However, these trajectories also raises important privacy concerns due to their strong …

Trajectory user linking (TUL) is a problem in trajectory classification that links anonymous
trajectories to the users who generated them. TUL has various uses such as identity …

Abstract Trajectory-User Linking (TUL), which aims to link the trajectories to the users who
have generated them, is critically important to many real applications. Existing approaches …

Data-driven decision making is becoming an integral part of manufacturing companies. Data
is collected and commonly used to improve efficiency and produce high quality items for the …

Recently, matching the cross-site user accounts based on user trajectory similarity has been
attracting much attention, which benefits many applications. Most of existing works measure …