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Data Mining in Homeland Security

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Chat Online. Bringing together biometric information with other types of information, to generate, through a process of cross matching and data mining, more or less detailed and specific profiles that will be. By taking advantage of the seemingly indefinite opportunities enabled by applications of data mining techniques. Originating in corporate business practices, data mining is multidisciplinary by nature and springs from several different disciplines including computer science, artificial intelligence, statistics, and biometrics. Using various approaches such as classification, clustering, association rules, and visualization , data mining has been gaining. Data mining is the process of searching through a large volume of data in an effort to discover patterns, trends, and relationships. Data mining is an umbrella term, and refers to a. Apr 27, The introduction of biometric voter registration and biometric voter identification on election day is a new trend in most African countries. This development in turn has necessitated massive political data mining. Data Mining in Homeland Security

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Data Mining in Homeland Security

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Stock photo. Brand new: Lowest price The lowest-priced brand-new, unused, unopened, undamaged item in its original packaging where packaging is applicable. This book is nothing less than a complete and comprehensive survey of the state-of-the-art of terrorism informatics.

Data Mining in Homeland Security

It systematically examines the current and ongoing research, including recent case studies and application of terrorism informatics techniques. See all 3 brand new listings. Buy It Now. Add to cart.

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About this product Product Information Terrorism informatics has been Daya as the application of advanced methodologies, information fusion and analysis techniques to acquire, integrate process, analyze, and manage the diversity of terrorism-related information for international and homeland security-related applications. The wide variety of methods used in terrorism informatics are Data Mining in Homeland Security from Computer Science, Informatics, Statistics, Mathematics, Linguistics, Social Sciences, and Public Policy and these methods are involved in the collection of huge amounts of information from varied and multiple sources and of many types in numerous languages. Information fusion and information technology analysis techniques--which include data mining, data integration, language translation technologies, and Swcurity and video processing--play central roles in the prevention, detection, and remediation of terrorism.

While there has been substantial investment on computer technology research applications to terrorism, much of the results and the literature has been a fragmented hodgepodge that is too narrowly focused on unconnected and unlinked discipline domains.

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As a result, there has been little effort to relate the research across the discipline domains from which terrorism informatics is drawn. The book will bring "knowledge" that can be used by scientists, security professionals, counterterrorism Data Mining in Homeland Security, and policy makers. The book will link organized into three major subject areas: Part I will focus on the methodological issues in terrorism research.

The methodological issues that impact trends, achievements, root causes, and failures in terrorism research will be treated within the context of the methods of retrieving and developing, sharing, and implementing terrorism informatics methodologies and resources. Part II will focus on three major areas of terrorism research: prevention, detection, and established governmental responses to terrorism. This section will systematically examine the current and ongoing research including recent case studies and application of terrorism informatics techniques.

Examples of such techniques are web mining, social network analysis, and multimodal event extraction, analysis to the terrorism phenomenon, etc.

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Additional Product Features Number of Volumes. Methodological Issues in Terrorism Research. From the reviews: "The title of this book might imply, at first sight, a US-centric approach to the topic, but in fact, the contributions are not only from the US, but also from Canada India, and Israel.]

Data Mining in Homeland Security

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