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 …

Spatiotemporal forecasting (STF) extends traditional time series forecasting or spatial
interpolation problem to space and time dimensions. Here, we review the statistical, physical …

Governments around the world have enforced strict guidelines on social interaction and
mobility to control the spread of the COVID-19 virus. Evidence has begun to emerge which …

Predicting crimes before they occur can save lives and losses of property. With the help of
machine learning, many researchers have studied predicting crimes extensively. In this …

Predicting crime using machine learning and deep learning techniques has gained
considerable attention from researchers in recent years, focusing on identifying patterns and …

This article examines the impact of new AI‐related technologies in data mining and big data
on important research questions in crime analytics. Because the field is so broad, the review …

Crime event analysis (CEA) has become increasingly important in assisting humans in
preventing future crimes. A fundamental challenge in the research community lies in the …

We systematically review the effectiveness of police presence. In doing so, we investigate
concepts of police presence and differences between reported effects. Using the Preferred …

Neural networks are a machine learning method that excel in solving classification and
forecasting problems. They have also been shown to be a useful tool for working with big …

Random cross-validation (CV) is often used to evaluate geospatial machine learning
models, particularly when a limited amount of sample data are available, and collecting an …