Data Mining, Southeast Asia Edition
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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It then covers in a chapter-by-chapter tour the concepts and techniques that
underlie classification, prediction, association, and clustering. These topics are
presented with examples, a tour of the best algorithms for each problem class,
and with ...
This explosive growth in stored or transient data has generated an urgent need
for new techniques and automated tools that can intelligently assist us in
transforming the vast amounts of data into useful information and knowledge.
This book ...
In addition to introducing the basic concepts, such as market basket analysis,
many techniques for frequent itemset mining are presented in an organized way.
These range from the basic Apriori algorithm and its variations to more advanced
The material in this book is presented from a database perspective, where
emphasis is placed on basic data mining concepts and techniques for
uncovering interesting data patterns hidden in large data sets. The
implementation methods ...
Database systems can be classified according to different criteria (such as data
models, or the types of data or applications involved), each of which may require
its own data mining technique. Data mining systems can therefore be classified ...
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8 Mining Stream TimeSeries and Sequence Data
9 Graph Mining Social Network Analysis and Multirelational Data Mining
10 Mining Object Spatial Multimedia Text and Web Data
11 Applications and Trends in Data Mining
An Introduction to Microsofts OLE DB for Data Mining