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Data mining and predictive analysis ...

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Data mining and predictive analysis = intelligence gathering and crime analysis /

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	Data mining and predictive analysis/ Colleen McCue.
其他題名:	intelligence gathering and crime analysis /
作者:	McCue, Colleen.
出版者:	Amsterdam ;Butterworth-Heinemann, : c2007.,
面頁冊數:	xxxi, 332 p. :ill., maps ;24 cm.
內容註:	Introductory Section -- Chapter 1: Basics -- Chapter 2: Domain Expertise -- Chapter 3: Data mining -- Methods -- Chapter 4: Process Models for Data Mining and Analysis -- Chapter 5: Data -- Chapter 6: Operationally-relevant preprocessing -- Chapter 7: Identification, Characterization and Modeling -- Chapter 8: Evaluation -- Chapter 9: Operationally-Actionable Output -- Applications -- Chapter 10: Normal Crime -- Chapter 11: Behavioral Analysis of Violent Crime -- Chapter 12: Risk and Threat Assessment -- Case Examples -- Chapter 13: Deployment -- Chapter 14: Surveillance Detection -- Advanced Concepts and Future Trends -- Chapter 15: Advanced Concepts in Data Mining -- Chapter 16: Future Trends.
標題:	Crime analysis. -
電子資源:	http://www.engineeringvillage.com/controller/servlet/OpenURL?genre=book&isbn=9780750677967An electronic book accessible through the World Wide Web; click for information
電子資源:	http://www.sciencedirect.com/science/book/9780750677967An electronic book accessible through the World Wide Web; click for information
電子資源:	http://www.loc.gov/catdir/enhancements/fy0646/2006040568-d.html
ISBN:	0750677961

Data mining and predictive analysis = intelligence gathering and crime analysis /
McCue, Colleen.

Data mining and predictive analysisintelligence gathering and crime analysis /[electronic resource] :Colleen McCue. - Amsterdam ;Butterworth-Heinemann,c2007. - xxxi, 332 p. :ill., maps ;24 cm.

Includes bibliographical references and index.

Introductory Section -- Chapter 1: Basics -- Chapter 2: Domain Expertise -- Chapter 3: Data mining -- Methods -- Chapter 4: Process Models for Data Mining and Analysis -- Chapter 5: Data -- Chapter 6: Operationally-relevant preprocessing -- Chapter 7: Identification, Characterization and Modeling -- Chapter 8: Evaluation -- Chapter 9: Operationally-Actionable Output -- Applications -- Chapter 10: Normal Crime -- Chapter 11: Behavioral Analysis of Violent Crime -- Chapter 12: Risk and Threat Assessment -- Case Examples -- Chapter 13: Deployment -- Chapter 14: Surveillance Detection -- Advanced Concepts and Future Trends -- Chapter 15: Advanced Concepts in Data Mining -- Chapter 16: Future Trends.

It is now possible to predict the future when it comes to crime. In Data Mining and Predictive Analysis, Dr. Colleen McCue describes not only the possibilities for data mining to assist law enforcement professionals, but also provides real-world examples showing how data mining has identified crime trends, anticipated community hot-spots, and refined resource deployment decisions. In this book Dr. McCue describes her use of "off the shelf" software to graphically depict crime trends and to predict where future crimes are likely to occur. Armed with this data, law enforcement executives can develop "risk-based deployment strategies," that allow them to make informed and cost-efficient staffing decisions based on the likelihood of specific criminal activity. Knowledge of advanced statistics is not a prerequisite for using Data Mining and Predictive Analysis. The book is a starting point for those thinking about using data mining in a law enforcement setting. It provides terminology, concepts, practical application of these concepts, and examples to highlight specific techniques and approaches in crime and intelligence analysis, which law enforcement and intelligence professionals can tailor to their own unique situation and responsibilities. * Serves as a valuable reference tool for both the student and the law enforcement professional * Contains practical information used in real-life law enforcement situations * Approach is very user-friendly, conveying sophisticated analyses in practical terms.

Electronic reproduction.
Amsterdam :
Elsevier Science & Technology,
2007.

Mode of access: World Wide Web.

ISBN: 0750677961

Source: 103995:104016Elsevier Science & Technologyhttp://www.sciencedirect.comSubjects--Topical Terms:

630972
Crime analysis.
Index Terms--Genre/Form:

542853
Electronic books.

LC Class. No.: HV7936.C88 / M37 2007eb

Dewey Class. No.: 363.25/6

Data mining and predictive analysis = intelligence gathering and crime analysis /
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505 0 $a Introductory Section -- Chapter 1: Basics -- Chapter 2: Domain Expertise -- Chapter 3: Data mining -- Methods -- Chapter 4: Process Models for Data Mining and Analysis -- Chapter 5: Data -- Chapter 6: Operationally-relevant preprocessing -- Chapter 7: Identification, Characterization and Modeling -- Chapter 8: Evaluation -- Chapter 9: Operationally-Actionable Output -- Applications -- Chapter 10: Normal Crime -- Chapter 11: Behavioral Analysis of Violent Crime -- Chapter 12: Risk and Threat Assessment -- Case Examples -- Chapter 13: Deployment -- Chapter 14: Surveillance Detection -- Advanced Concepts and Future Trends -- Chapter 15: Advanced Concepts in Data Mining -- Chapter 16: Future Trends.
520 $a It is now possible to predict the future when it comes to crime. In Data Mining and Predictive Analysis, Dr. Colleen McCue describes not only the possibilities for data mining to assist law enforcement professionals, but also provides real-world examples showing how data mining has identified crime trends, anticipated community hot-spots, and refined resource deployment decisions. In this book Dr. McCue describes her use of "off the shelf" software to graphically depict crime trends and to predict where future crimes are likely to occur. Armed with this data, law enforcement executives can develop "risk-based deployment strategies," that allow them to make informed and cost-efficient staffing decisions based on the likelihood of specific criminal activity. Knowledge of advanced statistics is not a prerequisite for using Data Mining and Predictive Analysis. The book is a starting point for those thinking about using data mining in a law enforcement setting. It provides terminology, concepts, practical application of these concepts, and examples to highlight specific techniques and approaches in crime and intelligence analysis, which law enforcement and intelligence professionals can tailor to their own unique situation and responsibilities. * Serves as a valuable reference tool for both the student and the law enforcement professional * Contains practical information used in real-life law enforcement situations * Approach is very user-friendly, conveying sophisticated analyses in practical terms.
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