Crime hotspot detection: A computational perspective

Emre Eftelioglu, Shashi Shekhar, Xun Tang

Research output: Chapter in Book/Report/Conference proceedingChapter

8 Scopus citations


Given a set of crime locations, a statistically significant crime hotspot is an area where the concentration of crimes inside is significantly higher than outside. The motivation of crime hotspot detection is twofold: detecting crime hotspots to focus the deployment of police enforcement and predicting the potential residence of a serial criminal. Crime hotspot detection is computationally challenging due to the difficulty of enumerating all potential hotspot areas, selecting an interest measure to compare these with the overall crime intensity, and testing for statistical significance to reduce chance patterns. This chapter focuses on statistical significant crime hotspots. First, the foundations of spatial scan statistics and its applications (i.e. SaTScan) to circular hotspot detection are reviewed. Next, ring-shaped hotspot detection is introduced. Third, linear hotspot detection is described since most crimes occur along a road network. The chapter concludes with future research directions in crime hotspot detection.

Original languageEnglish (US)
Title of host publicationData Mining Trends and Applications in Criminal Science and Investigations
PublisherIGI Global
Number of pages30
ISBN (Electronic)9781522504641
ISBN (Print)152250463X, 9781522504634
StatePublished - Jun 20 2016

Bibliographical note

Publisher Copyright:
© 2016 by IGI Global. All rights reserved.

Copyright 2017 Elsevier B.V., All rights reserved.


Dive into the research topics of 'Crime hotspot detection: A computational perspective'. Together they form a unique fingerprint.

Cite this