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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Results 1-5 of 66
... Data Mining: Concepts and Techniques, Second Edition Jiawei Han and Micheline Kamber Querying XML ... Spatial Databases: With Application to GIS Philippe Rigaux, Michel Scholl ... Data in Enterprise Databases: Binding Corporate Data to.
... Data 512 Mining Sequence Patterns in Biological Data 513 8.4.1 Alignment of Biological Sequences 514 8.4.2 Hidden ... Spatial, Multimedia, Text, and Web Data 591 10.1 Multidimensional Analysis and Descriptive Mining of Complex Data ...
... Spatial Data Mining 600 10.2.1 Spatial Data Cube Construction and Spatial OLAP 601 10.2.2 Mining Spatial Association and Co-location Patterns 605 10.2.3 Spatial Clustering Methods 606 10.2.4 Spatial Classification and Spatial Trend ...
Jiawei Han, Jian Pei, Micheline Kamber. mining object, spatial, multimedia, text, and Web data, which cover a great deal of new progress in these areas. Finally, in Chapter 11, we summarize the concepts presented in this book and discuss ...
... spatial, temporal, multimedia, active, stream, and sensor, and scientific and engineering databases, knowledge bases, and office information bases, have flourished. Issues related to the distribution, diversification, and sharing of data ...
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 |