Machine learning heavily relies on data, but real-world applications often encounter various
data-related issues. These include data of poor quality, insufficient data points leading to …

With the rapid development of low-cost consumer electronics and pervasive adoption of next
generation wireless communication technologies, a tremendous amount of data has been …

Trajectory data has the potential to greatly benefit a wide-range of real-world applications,
such as tracking the spread of the disease through people's movement patterns and …

Abstract Open Data Processing Services (ODPS) offers vast storage capacity and excellent
efficiency, which collects and stores a lot of data. As an essential component of ODPS …

Trajectory data collection is a common task with many applications in our daily lives.
Analyzing trajectory data enables service providers to enhance their services, which …

Fine-granular spatio-temporal trajectories, ie, time-stamped sequences of locations, play a
pivotal role in transport and urban analytics. However, sharing or publishing trajectory data …

Spatial Crowdsourcing (SC) has been an indispensable Location-based Service where the
SC server assigns tasks to workers based on the locations of task requesters and workers …

The w-event framework is the current standard for ensuring differential privacy on
continuously monitored data streams. Following the proposition of w-event differential …

Abstract Knowledge graph (KG) embedding methods are at the basis of many KG-based
data mining tasks, such as link prediction and node clustering. However, graphs may …

While location trajectories represent a valuable data source for analyses and location-based
services, they can reveal sensitive information, such as political and religious preferences …