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Data Mining Trends and Applications in Criminal Science and Investigations

Data Mining Trends and Applications in Criminal Science and Investigations

Omowunmi E. Isafiade, Antoine B. Bagula
Copyright: © 2016 |Pages: 386
ISBN13: 9781522504634|ISBN10: 152250463X|EISBN13: 9781522504641
DOI: 10.4018/978-1-5225-0463-4
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MLA

Isafiade, Omowunmi E., and Antoine B. Bagula, editors. Data Mining Trends and Applications in Criminal Science and Investigations. IGI Global, 2016. https://doi.org/10.4018/978-1-5225-0463-4

APA

Isafiade, O. E. & Bagula, A. B. (Eds.). (2016). Data Mining Trends and Applications in Criminal Science and Investigations. IGI Global. https://doi.org/10.4018/978-1-5225-0463-4

Chicago

Isafiade, Omowunmi E., and Antoine B. Bagula, eds. Data Mining Trends and Applications in Criminal Science and Investigations. Hershey, PA: IGI Global, 2016. https://doi.org/10.4018/978-1-5225-0463-4

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The field of data mining is receiving significant attention in today's information-rich society, where data is available from different sources and formats, in large volumes, and no longer constitutes a bottleneck for knowledge acquisition. This rich information has paved the way for novel areas of research, particularly in the crime data analysis realm.

Data Mining Trends and Applications in Criminal Science and Investigations presents scientific concepts and frameworks of data mining and analytics implementation and uses across various domains, such as public safety, criminal investigations, intrusion detection, crime scene analysis, and suspect modeling. Exploring the diverse ways that data is revolutionizing the field of criminal science, this publication meets the research needs of law enforcement professionals, data analysts, investigators, researchers, and graduate-level students.

Table of Contents

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Front Materials
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Title Page
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Copyright Page
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Advances in Data Mining and Database Management (ADMDM) Book Series
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Editorial Advisory Board and List of Reviewers
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Foreword
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Preface
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Acknowledgment
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Chapters
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Challenges and Existing Strategies in Public Safety and Crime Mining
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HotSpot, Spatial, and Visual Analytics
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Forensics, Suspect Modeling, and Intelligence Gathering
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Denial of Service, Cyber-Crime, and Intrusion Detection Management
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Back Materials
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Conclusion
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Compilation of References
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About the Contributors
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Index
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