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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... Schemas for Multidimensional Databases 114 3.2.3 Examples for Defining Star, Snowflake, and Fact Constellation Schemas 117 3.3 3.4 3.5 3.6 3.2.4 Measures: Their Categorization and Computation x Contents.
... schema at a single site in order to facilitate management decision making. Data warehouse technology includes data cleaning, data integration, and on-line analytical processing (OLAP), that is, analysis techniques with functionalities ...
... schemas or data structures, evaluate mined patterns, and visualize the patterns in different forms. From a data warehouse perspective, data mining can be viewed as an advanced stage of on-line analytical processing (OLAP). However, data ...
... schema, and that usually resides at a single site. Data warehouses are constructed via a process of data cleaning, data integration, data transformation, data loading, and periodic data refreshing. This process is discussed in Chapters ...
... 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 may be a relational data store or a multidimensional data cube. A data cube provides a ...
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 |