02090nam a2200349Ia 4500 20260803094046.0 251212s2007 xx 000 0 und d Introduction to business data mining / David Olson. Olson, David Shi, Yong New York : McGraw-Hill, 2007. xiii, 273 p.: 26 cm. Includes index 007-124470-0 Business Data processing Data mining 006.312 Ol84i 0 0 0 1 0 0 0 0 0 1 1 0 HED2579 English CollLib 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. 0 Text Unmediated Volume lcc BK rizal 2015-04-07 23:18:18 rizal 2015-04-07 23:18:18 3422 3409 3409 0 0 ddc 0 0 HED HED HED 2025-12-21 006.312 Ol84i HED2579 2026-06-02 00:00:00 2025-12-21 BK