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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... frequently sold together. The mining of such frequent patterns for transactional data is discussed in Chapter 5. Advanced. Data. and. Information. Systems. and. Advanced. Applications. Relational database systems have been widely used in ...
... frequent patterns with that at a certain previous time. Most stream data reside at a rather low level of abstraction, whereas analysts are often more interested in higher and multiple levels of abstraction. Thus, multilevel ...
... Patterns,. Associations,. and. Correlations. Frequent patterns, as the name suggests, are patterns that occur frequently in data. There are many kinds of frequent patterns, including itemsets, subsequences, and substructures. A frequent ...
... Frequent itemset mining is the simplest form of frequent pattern mining. The mining of frequent patterns, associations, and correlations is discussed in Chapter 5, where particular emphasis is placed on efficient algorithms for frequent ...
... patterns (such as buying preference, buying time, budget cycles, and appetites for spending); (2) repositioning ... frequent queries, especially for queries requiring aggregations. Data warehousing provides an interesting alternative to ...
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 |