Knowledge Discovery in Multiple Databases (Advanced Information and Knowledge Processing) - Hardcover

Zhang, Shichao; Zhang, Chengqi; Wu, Xindong

Hardcover

ISBN 10: 1852337036 ISBN 13: 9781852337032

Publisher: Springer London Ltd, 2004

Synopsis

The Web has emerged as a large, distributed data repository, & information on the Internet & in existing transaction databases can be analyzed for commercial gains in decision making. Therefore, how to efficiently identify quality knowledge from different data sources uncovers a significant challenge. Knowledge Discovery in Multiple Databases provides a comprehensive introduction to the latest advancements in multi-database mining, & presents a local-pattern analysis framework for pattern discovery from multiple data sources. Based on this framework, data preparation techniques in multiple databases, an application-independent database classification for data reduction, & efficient algorithms for pattern discovery from multiple databases are described. This book is suitable for researchers, professionals & students in data mining, distributed data analysis, and machine learning. It is also appropriate for use as a text supplement for broader courses involving knowledge discovery in databases & data mining.

About this title

Review

From the reviews:

"The book contains the latest on research in database multi-mining (32 papers published after 2000) and offers for consideration a local-pattern analysis framework for pattern discovery from multiple data sources. Starting from the local pattern in multiple data bases, the authors propose ... a new pattern named ‘high-vote’ pattern based on statistical analysis of vote ratio received by a pattern from each branch of the company." (Silviu Craciunas, Zentralblatt MATH, Vol. 1067, 2005)

Synopsis

The Web has emerged as a large, distributed data repository, and information on the Internet and in existing transaction databases can be analyzed for commercial gains in decision making. Therefore, how to efficiently identify quality knowledge from different data sources uncovers a significant challenge. This challenge has attracted wide interest from both academia and the industry. "Knowledge Discovery in Multiple Databases" provides a comprehensive introduction to the latest advancements in multi-database mining, and presents a local-pattern analysis framework for pattern discovery from multiple data sources. Based on this framework, data preparation techniques in multiple databases, an application-independent database classification for data reduction, and efficient algorithms for pattern discovery from multiple databases are described. "Knowledge Discovery in Multiple Databases" is suitable for researchers, professionals and students in data mining, distributed data analysis, and machine learning, who are interested in multi-database mining.

It is also appropriate for use as a text supplement for broader courses that might involve knowledge discovery in databases and data mining.

Edition details

• Publisher: Springer London Ltd
• Publication date: 2004
• Language: English
• ISBN 10: 1852337036
• ISBN 13: 9781852337032
• Binding: Hardcover
• Number of pages: 245