Irregular time series data is becoming increasingly prevalent with the growth of multi-sensor
systems as well as the continued use of unstructured manual data recording mechanisms …

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 …

Accurate forecasting of citywide traffic flow has been playing critical role in a variety of
spatial-temporal mining applications, such as intelligent traffic control and public risk …

Insider threats, as one type of the most challenging threats in cyberspace, usually cause
significant loss to organizations. While the problem of insider threat detection has been …

Events are occurrences in specific locations, time, and semantics that nontrivially impact
either our society or the nature, such as earthquakes, civil unrest, system failures …

Session-based recommendation plays a central role in a wide spectrum of online
applications, ranging from e-commerce to online advertising services. However, the majority …

Crime has become a major concern in many cities, which calls for the rising demand for
timely predicting citywide crime occurrence. Accurate crime prediction results are vital for the …

Short-term traffic flow forecasting at isolated points is a fundamental yet challenging task in
many intelligent transportation systems. We present a novel long short-term memory (LSTM) …

Urban flow prediction benefits smart cities in many aspects, such as traffic management and
risk assessment. However, a critical prerequisite for these benefits is having fine-grained …

The security of a community is its topmost priority; hence, governments must take proper
actions to reduce the crime rate. Consequently, the application of artificial intelligence (AI) in …