Crime data mining: a general framework and some examples

By Hsinchun Chen, Wingyan Chung, Jennifer Jie Xu, G. Wang, Yi Qin, Michael Chau. Computer, 2004

604 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Information Systems

View Paper: https://www.semanticscholar.org/paper/190036bdec136f8795493ac590f6c2d4f0134065

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Citations in the corpus

Data Mining for the Internet of Things: Literature Review and Challenges (2015, background): “law-enforcement is how to quickly analyze the growing volumes of crime data [127].”
GOTCHA! Network-Based Fraud Detection for Social Security Fraud (2017, background): “2001) telecom fraud X X 4 (Chen et al. 2004) insurance fraud X”
Data Matching (2012, background): “gence agents need to be able to find the details of suspects in real time while at the same time allowing approximate matching of personal details [54, 91, 267].”
Mining communities and their relationships in blogs: A study of online hate groups (2007, methodology): “In recent years, advanced techniques such as text mining, Web mining, and social network analysis have been widely used in studies on cyber crimes, online extremist groups, and terrorist organizations (e.g., Burris et al., 2000, Chen et al., 2004, Zhou et al., 2005).”
Learning to Detect Patterns of Crime (2013, methodology): “[12], in which the authors present a general framework for crime data mining, where many of these standard tools are available as part of the COPLINK [13] software package.”
Digital technologies and artificial intelligence’s present and foreseeable impact on lawyering, judging, policing and law enforcement (2015, methodology): “Chen et al. (2004) used a concept-space approach, in order to extract criminal relations from the incident summaries and create a likely network of suspects.”
Clique Relaxations in Social Network Analysis: The Maximum k-Plex Problem (2011, background): “Concepts of social network analysis provide suitable data mining tools for this purpose [17].”
A process for predicting manhole events in Manhattan (2010, methodology): “Chen et al. (2004) designed a system for several problems in crime data mining in collaboration with the Tucson police department.”