With the advancement of telecommunications, sensor networks, crowd sourcing, and remote
sensing technology in present days, there has been a tremendous growth in the volume of …

Spatio-temporal data usually records the states over time of an object, an event or a position
in space. Spatio-temporal data can be found in several application fields, such as traffic …

Large volumes of spatio-temporal data are increasingly collected and studied in diverse
domains, including climate science, social sciences, neuroscience, epidemiology …

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

Spatiotemporal data mining aims to discover interesting, useful but non-trivial patterns in big
spatial and spatiotemporal data. They are used in various application domains such as …

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

The spatio-temporal database (STDB) has received considerable attention during the past
few years, due to the emergence of numerous applications (eg, flight control systems …

With the growth in the size of datasets, data mining has recently become an important
research topic and is receiving substantial interest from both academia and industry. At the …

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 …

In the era of massive data, people are paying more and more attention to the spatio-
temporal attributes of data. Many studies have begun to explore the methods of spatio …