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Data Mining And Predictive Analysis

Author: Colleen McCue
Publisher: Elsevier
ISBN: 9780080464626
Size: 54.75 MB
Format: PDF
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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

Predictive Analytics

Author: Eric Siegel
Publisher: John Wiley & Sons
ISBN: 1118416856
Size: 14.61 MB
Format: PDF, Docs
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“Mesmerizing & fascinating...” —The Seattle Post-Intelligencer "The Freakonomics of big data." —Stein Kretsinger, founding executive of Advertising.com Award-winning | Used by over 30 universities | Translated into 9 languages An introduction for everyone. In this rich, fascinating — surprisingly accessible — introduction, leading expert Eric Siegel reveals how predictive analytics works, and how it affects everyone every day. Rather than a “how to” for hands-on techies, the book serves lay readers and experts alike by covering new case studies and the latest state-of-the-art techniques. Prediction is booming. It reinvents industries and runs the world. Companies, governments, law enforcement, hospitals, and universities are seizing upon the power. These institutions predict whether you're going to click, buy, lie, or die. Why? For good reason: predicting human behavior combats risk, boosts sales, fortifies healthcare, streamlines manufacturing, conquers spam, optimizes social networks, toughens crime fighting, and wins elections. How? Prediction is powered by the world's most potent, flourishing unnatural resource: data. Accumulated in large part as the by-product of routine tasks, data is the unsalted, flavorless residue deposited en masse as organizations churn away. Surprise! This heap of refuse is a gold mine. Big data embodies an extraordinary wealth of experience from which to learn. Predictive Analytics unleashes the power of data. With this technology, the computer literally learns from data how to predict the future behavior of individuals. Perfect prediction is not possible, but putting odds on the future drives millions of decisions more effectively, determining whom to call, mail, investigate, incarcerate, set up on a date, or medicate. In this lucid, captivating introduction — now in its Revised and Updated edition — former Columbia University professor and Predictive Analytics World founder Eric Siegel reveals the power and perils of prediction: What type of mortgage risk Chase Bank predicted before the recession. Predicting which people will drop out of school, cancel a subscription, or get divorced before they even know it themselves. Why early retirement predicts a shorter life expectancy and vegetarians miss fewer flights. Five reasons why organizations predict death — including one health insurance company. How U.S. Bank and Obama for America calculated — and Hillary for America 2016 plans to calculate — the way to most strongly persuade each individual. Why the NSA wants all your data: machine learning supercomputers to fight terrorism. How IBM's Watson computer used predictive modeling to answer questions and beat the human champs on TV's Jeopardy! How companies ascertain untold, private truths — how Target figures out you're pregnant and Hewlett-Packard deduces you're about to quit your job. How judges and parole boards rely on crime-predicting computers to decide how long convicts remain in prison. 183 examples from Airbnb, the BBC, Citibank, ConEd, Facebook, Ford, Google, the IRS, LinkedIn, Match.com, MTV, Netflix, PayPal, Pfizer, Spotify, Uber, UPS, Wikipedia, and more. How does predictive analytics work? This jam-packed book satisfies by demystifying the intriguing science under the hood. For future hands-on practitioners pursuing a career in the field, it sets a strong foundation, delivers the prerequisite knowledge, and whets your appetite for more. A truly omnipresent science, predictive analytics constantly affects our daily lives. Whether you are a consumer of it — or consumed by it — get a handle on the power of Predictive Analytics.

Journeys To Data Mining

Author: Mohamed Medhat Gaber
Publisher: Springer Science & Business Media
ISBN: 3642280471
Size: 64.19 MB
Format: PDF, ePub
View: 6008
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Data mining, an interdisciplinary field combining methods from artificial intelligence, machine learning, statistics and database systems, has grown tremendously over the last 20 years and produced core results for applications like business intelligence, spatio-temporal data analysis, bioinformatics, and stream data processing. The fifteen contributors to this volume are successful and well-known data mining scientists and professionals. Although by no means an exhaustive list, all of them have helped the field to gain the reputation and importance it enjoys today, through the many valuable contributions they have made. Mohamed Medhat Gaber has asked them (and many others) to write down their journeys through the data mining field, trying to answer the following questions: 1. What are your motives for conducting research in the data mining field? 2. Describe the milestones of your research in this field. 3. What are your notable success stories? 4. How did you learn from your failures? 5. Have you encountered unexpected results? 6. What are the current research issues and challenges in your area? 7. Describe your research tools and techniques. 8. How would you advise a young researcher to make an impact? 9. What do you predict for the next two years in your area? 10. What are your expectations in the long term? In order to maintain the informal character of their contributions, they were given complete freedom as to how to organize their answers. This narrative presentation style provides PhD students and novices who are eager to find their way to successful research in data mining with valuable insights into career planning. In addition, everyone else interested in the history of computer science may be surprised about the stunning successes and possible failures computer science careers (still) have to offer.

Emerging Methods In Predictive Analytics Risk Management And Decision Making

Author: Hsu, William H.
Publisher: IGI Global
ISBN: 1466650648
Size: 35.12 MB
Format: PDF, Mobi
View: 6483
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Decision making tools are essential for the successful outcome of any organization. Recent advances in predictive analytics have aided in identifying particular points of leverage where critical decisions can be made. Emerging Methods in Predictive Analytics: Risk Management and Decision Making provides an interdisciplinary approach to predictive analytics; bringing together the fields of business, statistics, and information technology for effective decision making. Managers, business professionals, and decision makers in diverse fields will find the applications and cases presented in this text essential in providing new avenues for risk assessment, management, and predicting the future outcomes of their decisions.

Getting Started With Business Analytics

Author: David Roi Hardoon
Publisher: CRC Press
ISBN: 1439896542
Size: 71.99 MB
Format: PDF, Docs
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Assuming no prior knowledge or technical skills, Getting Started with Business Analytics: Insightful Decision-Making explores the contents, capabilities, and applications of business analytics. It bridges the worlds of business and statistics and describes business analytics from a non-commercial standpoint. The authors demystify the main concepts and terminologies and give many examples of real-world applications. The first part of the book introduces business data and recent technologies that have promoted fact-based decision-making. The authors look at how business intelligence differs from business analytics. They also discuss the main components of a business analytics application and the various requirements for integrating business with analytics. The second part presents the technologies underlying business analytics: data mining and data analytics. The book helps you understand the key concepts and ideas behind data mining and shows how data mining has expanded into data analytics when considering new types of data such as network and text data. The third part explores business analytics in depth, covering customer, social, and operational analytics. Each chapter in this part incorporates hands-on projects based on publicly available data. Helping you make sound decisions based on hard data, this self-contained guide provides an integrated framework for data mining in business analytics. It takes you on a journey through this data-rich world, showing you how to deploy business analytics solutions in your organization.

Investigative Data Mining For Security And Criminal Detection

Author: Jesus Mena
Publisher: Elsevier
ISBN: 008050938X
Size: 69.81 MB
Format: PDF, Kindle
View: 6632
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Investigative Data Mining for Security and Criminal Detection is the first book to outline how data mining technologies can be used to combat crime in the 21st century. It introduces security managers, law enforcement investigators, counter-intelligence agents, fraud specialists, and information security analysts to the latest data mining techniques and shows how they can be used as investigative tools. Readers will learn how to search public and private databases and networks to flag potential security threats and root out criminal activities even before they occur. The groundbreaking book reviews the latest data mining technologies including intelligent agents, link analysis, text mining, decision trees, self-organizing maps, machine learning, and neural networks. Using clear, understandable language, it explains the application of these technologies in such areas as computer and network security, fraud prevention, law enforcement, and national defense. International case studies throughout the book further illustrate how these technologies can be used to aid in crime prevention. Investigative Data Mining for Security and Criminal Detection will also serve as an indispensable resource for software developers and vendors as they design new products for the law enforcement and intelligence communities. Key Features: * Covers cutting-edge data mining technologies available to use in evidence gathering and collection * Includes numerous case studies, diagrams, and screen captures to illustrate real-world applications of data mining * Easy-to-read format illustrates current and future data mining uses in preventative law enforcement, criminal profiling, counter-terrorist initiatives, and forensic science * Introduces cutting-edge technologies in evidence gathering and collection, using clear non-technical language * Illustrates current and future applications of data mining tools in preventative law enforcement, homeland security, and other areas of crime detection and prevention * Shows how to construct predictive models for detecting criminal activity and for behavioral profiling of perpetrators * Features numerous Web links, vendor resources, case studies, and screen captures illustrating the use of artificial intelligence (AI) technologies

Encyclopedia Of Cybercrime

Author: Samuel C. McQuade
Publisher: Greenwood
ISBN:
Size: 12.11 MB
Format: PDF
View: 1761
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There are today no more compelling sets of crime and security threats than those encompassed by cybercrime.