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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... Multidimensional Data Model 110 3.2.1 From Tables and Spreadsheets to Data Cubes 110 3.2.2 Stars, Snowflakes, and Fact Constellations: Schemas for Multidimensional Databases 114 3.2.3 Examples for Defining Star, Snowflake, and Fact ...
... Multidimensional Data Model 123 3.2.7 A Starnet Query Model for Querying Multidimensional Databases 126 Data Warehouse Architecture 127 3.3.1 Steps for the Design and Construction of Data Warehouses 128 3.3.2 A Three-Tier Data Warehouse ...
... Multidimensional Association Rules from Relational Databases and Data Warehouses 254 From Association Mining to Correlation Analysis 259 5.4.1 Strong Rules Are Not Necessarily Interesting: An Example 260 5.4.2 From Association Analysis ...
... Multidimensional Analysis of Multimedia Data 609 10.3.3 Classification and Prediction Analysis of Multimedia Data 611 10.3.4 Mining Associations in Multimedia Data 612 10.3.5 Audio and Video Data Mining 613 Text Mining 614 10.4.1 Text ...
... multidimensional association rules, and quantitative association rules. In comparison with the previous edition, this chapter has placed greater emphasis on the generation of meaningful association and correlation rules. Strategies for ...
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 |