Data Mining, Southeast Asia EditionElsevier, 2006 M04 6 - 800 pages Our ability to generate and collect data has been increasing rapidly. Not only are all of our business, scientific, and government transactions now computerized, but the widespread use of digital cameras, publication tools, and bar codes also generate data. On the collection side, scanned text and image platforms, satellite remote sensing systems, and the World Wide Web have flooded us with a tremendous amount of data. This explosive growth has generated an even more urgent need for new techniques and automated tools that can help us transform this data into useful information and knowledge. Like the first edition, voted the most popular data mining book by KD Nuggets readers, this book explores concepts and techniques for the discovery of patterns hidden in large data sets, focusing on issues relating to their feasibility, usefulness, effectiveness, and scalability. However, since the publication of the first edition, great progress has been made in the development of new data mining methods, systems, and applications. This new edition substantially enhances the first edition, and new chapters have been added to address recent developments on mining complex types of data— including stream data, sequence data, graph structured data, social network data, and multi-relational data.
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Jiawei Han, Jian Pei, Micheline Kamber. The Morgan Kaufmann Series in Data Management Systems Series Editor: Jim Gray, Microsoft Research Data Mining: Concepts and Techniques, Second Edition Jiawei Han and Micheline Kamber Querying XML ...
Jiawei Han, Jian Pei, Micheline Kamber. Managing Reference Data in Enterprise Databases: Binding Corporate Data to the Wider World Malcolm Chisholm Data Mining ... Database Systems: Triggers and Rules For Advanced Database Processing.
... Database Systems Edited by Johann Christoph Freytag, David Maier, and Gottfried Vossen Transaction Processing: Concepts and Techniques Jim Gray and Andreas Reuter Building an Object-Oriented Database System: The Story of O2 Edited by ...
... Data Mining Systems 29 1.7 Data Mining Task Primitives 31 Integration of a Data Mining System with a Database or Data Warehouse System 34 1.9 Major Issues in Data Mining 36 Chapter 2 Chapter 3 1.10 Summary 39 Exercises 40 Bibliographic ...
... Data 94 Summary 97 Exercises 97 Bibliographic Notes 101 Data Warehouse and OLAP Technology: An Overview 105 3.1 3.2 What Is a Data Warehouse? 105 3.1.1 Differences between Operational Database Systems and Data Warehouses 108 3.1.2 But ...
Contents
1 | |
47 | |
105 | |
4 Data Cube Computation and Data Generalization | 157 |
5 Mining Frequent Patterns Associations and Correlations | 227 |
6 Classification and Prediction | 285 |
7 Cluster Analysis | 383 |
8 Mining Stream TimeSeries and Sequence Data | 467 |
9 Graph Mining Social Network Analysis and Multirelational Data Mining | 535 |
10 Mining Object Spatial Multimedia Text and Web Data | 591 |
11 Applications and Trends in Data Mining | 649 |
An Introduction to Microsofts OLE DB for Data Mining | 691 |
Bibliography | 703 |
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Geographic Data Mining and Knowledge Discovery Harvey J. Miller,Jiawei Han No preview available - 2003 |