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Visual Analytics for Crime Analysis and Decision Support

Visual Analytics for Crime Analysis and Decision Support
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Author(s): Chih-Hao Ku (Lawrence Technological University, USA), Alicia Iriberri (California State University, Fresno, USA)and Goutam Jena (Lawrence Technological University, USA)
Copyright: 2017
Pages: 24
Source title: Decision Management: Concepts, Methodologies, Tools, and Applications
Source Author(s)/Editor(s): Information Resources Management Association (USA)
DOI: 10.4018/978-1-5225-1837-2.ch065

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Abstract

Today, the amount of digital data increases exponentially due to the rapid growth of the Internet, mobile, and sensory data. Crime data are arriving from multiple sources and formats. The major challenge for crime analysis is to store, manipulate, manage, and analyze data efficiently. To gain useful insight from a great amount of raw data, visual analytics techniques have been drawn attention to law enforcement agencies and researchers. The visual analytics applications do not erase the need for crime analysts' insight. To make better predictions and smarter decisions, data mining, text mining, information visualization, human-computer interaction, and analytics techniques are important to explore. This book chapter provides an overview of different types of crime data, discusses how to analyze and visualize different types of data, and explores popular visualization toolkits that have been used for crime analysis.

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