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Skip to search form Skip to main content You are currently offline. Some features of the site may not work correctly. Berry Published Computer Science. The leading introductory book on data mining, fully updated and revised! When Berry and Linoff wrote the first edition of Data Mining Techniques in the late s, data mining was just starting to move out of the lab and into the office and has since grown to become an indispensable tool of modern business.
View PDF. Save to Library. Create Alert. Launch Research Feed. Share This Paper. Topics from this paper. Customer relationship management Data mining. Purchasing Confusion. Citations Publications citing this paper. Menon , Saurabh Chandra Discovering customer value for marketing systems: an empirical case study Wen-Yu Chiang Engineering Applying data mining with a new model on customer relationship management systems: a case of airline industry in Taiwan Wen-Yu Chiang Engineering Applications of data mining techniques for churn prediction and cross-selling in the telecommunications industry Emad Hanif Computer Science Exploring value creation through web mining : a case study on the online weather forecast business Jun Che Related Papers.
Data Mining Techniques: For Marketing, Sales, and Customer Relationship Management, 3rd Edition
Skip to search form Skip to main content You are currently offline. Some features of the site may not work correctly. Berry Published Computer Science. The leading introductory book on data mining, fully updated and revised!
Data Mining Techniques: For Marketing, Sales, and Customer Relationship Management
Michael J. Berry , Gordon S. Packed with more than forty percent new and updated material, this edition shows business managers, marketing analysts, and data mining specialists how to harness fundamental data mining methods and techniques to solve common types of business problems Each chapter covers a new data mining technique, and then shows readers how to apply the technique for improved marketing, sales, and customer support The authors build on their reputation for concise, clear, and practical explanations of complex concepts, making this book the perfect introduction to data mining More advanced chapters cover such topics as how to prepare data for analysis and how to create the necessary infrastructure for data mining Covers core data mining techniques, including decision trees, neural networks, collaborative filtering, association rules, link analysis, clustering, and survival analysis. The Virtuous Cycle of Data Mining. Data Mining Methodology and Best Practices. Hypothesis Testing.