
Real-World Data Mining
Description
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Use the latest data mining best practices to enable timely, actionable, evidence-based decision making throughout your organization! Real-World Data Mining demystifies current best practices, showing how to use data mining to uncover hidden patterns and correlations, and leverage these to improve all aspects of business performance.
Drawing on extensive experience as a researcher, practitioner, and instructor, Dr. Dursun Delen delivers an optimal balance of concepts, techniques and applications. Without compromising either simplicity or clarity, he provides enough technical depth to help readers truly understand how data mining technologies work. Coverage includes: processes, methods, techniques, tools, and metrics; the role and management of data; text and web mining; sentiment analysis; and Big Data integration. Throughout, Delen's conceptual coverage is complemented with application case studies (examples of both successes and failures), as well as simple, hands-on tutorials.
Real-World Data Mining will be valuable to professionals on analytics teams; professionals seeking certification in the field; and undergraduate or graduate students in any analytics program: concentrations, certificate-based, or degree-based.
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Person
Dr. Delen holds William S. Spears and Neal Patterson Endowed Chairs in Business Analytics, and he is Director of Research for the Center for Health Systems Innovation and Professor of Management Science and Information Systems in the Spears School of Business at Oklahoma State University. His research has appeared in major journals, including Decision Sciences, Decision Support Systems, Communications of the ACM, Computers and Operations Research, Computers in Industry, Journal of Production Operations Management, Artificial Intelligence in Medicine, and Expert Systems with Applications, among others. He has recently published six books: Advanced Data Mining Techniques (Springer, 2008), Decision Support and Business Intelligence Systems (Prentice Hall, 2010), Business Intelligence: A Managerial Approach (Prentice Hall, 2010), Practical Text Mining and Statistical Analysis for Non-structured Text Data Applications (Elsevier, 2012), Business Intelligence: A Managerial Perspective on Analytics, 3rd edition (Prentice Hall, 2013), and Business Intelligence and Analytics: Systems for Decision Support, 10th edition (Prentice Hall, 2014). He served as the general co-chair for the fourth International Conference on Network Computing and Advanced Information Management, and he regularly chairs tracks and mini-tracks at various information systems conferences. He also serves as associate editor-in-chief, senior editor, associate editor, and editorial board member on a dozen academic and technical journals.
Content
Chapter 1: Introduction to Analytics 1
Chapter 2: Introduction to Data Mining 31
Chapter 3: The Data Mining Process 67
Chapter 4: Data and Methods in Data Mining 93
Chapter 5: Data Mining Algorithms 141
Chapter 6: Text Analytics and Sentiment Analysis 183
Chapter 7: Big Data Analytics 231
Index 265
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