3 accepted papers
With the rise of social media and Location-Based Social Networks (LBSN), check-in data across platforms has become crucial for User Identity Linkage (UIL). These data not only reveal users' spatio-temporal information but also provide insights into their behavior patterns and interests. However, cro…
Trajectory-user linking (TUL) aims to match anonymous trajectories to the most likely users who generated them, offering benefits for a wide range of real-world spatio-temporal applications. However, existing TUL methods are limited by high model complexity and poor learning of the effective represe…
Inferring social relationships from human mobility data holds significant value in real-life spatio-temporal applications, which inspires the development of a series of graph-based methods for inferring social relationships. Despite their effectiveness, we argue that previous methods either rely sol…