ForewordPrefaceChapter1 Introduction 1.1 What Motivated Data Mining? Why Is It Important? 1.2 So,What Is Data Mining? 1.3 Data Mining-On What Kind of Data? 1.4 Data Mining Functionalities-What Kinds of Patterns Can Be Mined? 1.5 Are All of the Patterns Interesting? 1.6 Classification of Data Mining Systems 1.7 Major Issues in Data Mining 1.8 Summary Exercises Bibliographic NotesChapter2 Data Warehouse and LOAP Technology for Data Mining 2.1 What Is a Data Warehouse? 2.2 A Multidimensional Data Model 2.3 Data Warehouse Architecture 2.4 Data Warehouse Implementation 2.5 Further Development of Data Cube Technology 2.6 From Data Warehousing to Data Mining 2.7 Summary Exercises Bibliographic NotesChapter3 Data Preprocessing 3.1 Why Preprocess the Data? 3.2 Data Cleaning 3.3 Data Integration and Transformation 3.4 Data Reduction 3.5 Discretization and Concept Hierarchy Generation 3.6 Summary Exercises Bibliographic NotesChapter4 Data Mining Primitives，Languages，and System ArchitecturesChapter5 Concept Description：Characterization and ComparisonChapter6 Mining Association Rules in Large DatabasesChapter7 Classification and PredictionChapter8 Cluster AnalysisChapter9 Mining Comples Types of DataChapter10 Applications and Trends in Data MiningAppendix A Introduction to Microsoft’s OLE DB for Data MiningAppendix B An Introduction to BDMiner BibliographyIndex