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.
|
From inside the book
Results 1-5 of 81
... performed, the types of patterns that can be found, and how to tell which patterns represent useful knowledge. You will study data mining primitives, from which data mining query languages can be designed. Issues regarding how to ...
... performed before the data selection process, particularly in the case of data warehousing. Data reduction may also be performed to obtain a smaller representation of the original data without sacrificing its integrity. 1.2 So, What Is ...
... performing exploratory data mining based on the intermediate data mining results. In addition, this component allows ... performed. In principle, data mining should be applicable to any kind of data repository, as well as to transient ...
... performed on spatial databases?” you may ask. Data mining may uncover patterns describing the characteristics of houses located near a specified kind of location, such as a park, for instance. Other patterns may describe the climate of ...
... performing statistical data distribution and correlation analysis, and transforming the given data into higher, more ... performed. Data. Streams. Many applications involve the generation and analysis of a new kind of data, calledstream ...
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 |
Other editions - View all
Common terms and phrases
Popular passages
References to this book
Geographic Data Mining and Knowledge Discovery Harvey J. Miller,Jiawei Han No preview available - 2003 |