Introduction to business data mining /
David Olson.
- New York : McGraw-Hill, 2007.
- xiii, 273 p.: 26 cm.
Includes index
Part I: INTRODUCTION 1: Initial Description of Data Mining in Business 2: Data Mining Processes and Knowledge Discovery 3: Database Support to Data Mining Part II: DATA MINING METHODS AS TOOLS 4: Overview of Data Mining Techniques 4 Appendix: Enterprise Miner Demonstration on Expenditure Data Set 5: Cluster Analysis 5 Appendix: Clementine 6: Regression Algorithms in Data Mining 7: Neural Networks in Data Mining 8: Decision Tree Algorithms 8 Appendix: Demonstration of See5 Decision Tree Analysis 9: Linear Programming-Based Methods 9 Appendix: Data Mining Linear Programming Formulations Part III: BUSINESS APPLICATIONS 10: Business Data Mining Applications Applications 11: Market-Basket Analysis 11 Appendix: Market-Basket Procedure Part IV: DEVELOPING ISSUES 12: Text and Web Mining 12 Appendix: Semantic Text Analysis 13: Ethical Aspects of Data Mining
Introduces students to the fundamental concepts of data mining. This text shows readers how to gather and analyze large sets of data to gain useful business understanding. It also describes and demonstrated basic data mining algorithms, and presents an overview of the developing areas in this field, including web mining, text mining, and more.