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 80
... Structure 173 4.1.5 Precomputing Shell Fragments for Fast High-Dimensional OLAP 178 4.1.6 Computing Cubes with Complex Iceberg Conditions 187 Further Development of Data Cube and OLAP Technology 189 4.2.1 Discovery-Driven Exploration of ...
... Structure 420 7.6.3 DENCLUE: Clustering Based on Density Distribution Functions 422 7.7 Grid-Based Methods 424 7.7.1 STING: STatistical INformation Grid 425 7.7.2 WaveCluster: Clustering Using Wavelet Transformation 427 7.8 Model-Based ...
... Structure 630 10.5.2 Mining the Web's Link Structures to Identify Authoritative Web Pages 631 10.5.3 Mining Multimedia Data on the Web 637 10.5.4 Automatic Classification of Web Documents 638 10.5.5 Web Usage Mining 640 Summary 641 ...
... structure, where each dimension corresponds to an attribute or a set of attributes in the schema, and each cell stores the value of some aggregate measure, such as count or sales amount. The actual physical structure of a data warehouse ...
... structures and scalable methods for handling complex object structures; variable-length records; semistructured or unstructured data; text, spatiotemporal, and multimedia data; and database schemas with complex structures and dynamic ...
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 |