The advancements of sensing technologies, including remote sensing, in situ sensing,
social sensing, and health sensing, have tremendously improved our capability to observe …

Big Data have emerged and become the norm in the past decade with its well-known 4V
challenges and now adds value (a 5th V) for scientific research and the development of new …

A key challenge in mining social media data streams is to identify events which are actively
discussed by a group of people in a specific local or global area. Such events are useful for …

Explosive growth in geospatial and temporal data as well as the emergence of new
technologies emphasize the need for automated discovery of spatiotemporal knowledge …

With the fast development of various positioning techniques such as Global Position System
(GPS), mobile devices and remote sensing, spatio-temporal data has become increasingly …

Spatiotemporal data mining (STDM) discovers useful patterns from the dynamic interplay
between space and time. Several available surveys capture STDM advances and report a …

The tremendous growth of event dissemination over social networks makes it very
challenging to accurately discover and track exciting events, as well as their evolution and …

As the volume, variety, and veracity of spatio-temporal datasets increase, traditional
statistical methods for dealing with such data are becoming overwhelmed. Nevertheless …

Social media streams and remote sensing data have emerged as new sources for tracking
disaster events, and assessing their damages. Previous studies focus on a case-by-case …

Event detection is a critical task in sensor networks for a variety of real-world applications.
Many realworld events often exhibit complex spatio-temporal patterns whereby they …