With the continued deployment of the Internet of Things (IoT), increasing volumes of devices
are being deployed that emit massive spatially referenced data. Due in part to the dynamic …

Within the rapidly expanding Internet of Things (IoT), growing amounts of spatially
referenced data are being generated. Due to the dynamic, decentralized, and …

Participatory sensing has emerged as a new data collection paradigm, in which humans use
their own devices (cell phone accelerometers, cameras, etc.) as sensors. This paradigm …

Abstract Development and wide acceptance of data-driven applications in many aspects of
our daily lives is generating waste volume of diverse data, which can be collected and …

The ubiquity and complexity of spatial-temporal trajectory data have made it challenging to
efficiently store and query such data. Furthermore, the increasing number of users also …

Our modern society is struggling with an unprecedented amount of online misinformation,
which does harm to democracy, economics, and cybersecurity. Journalism and politics have …

The PreDeCon clustering algorithm finds arbitrarily shaped clusters in high-dimensional
feature spaces, which remains an active research topic with many potential applications …

Spatial-temporal trajectory data contains rich information about moving objects and
phenomena, hence have been widely used for a great number of real-world applications …