-------- Original-Nachricht -------- Betreff: [isworld] New book announcement: Post-Mining of Association Rules - Techniques for Effective Knowledge Extraction Datum: Sat, 13 Jun 2009 00:10:39 +0000 Von: Yanchang Zhao zhaoyanchang@hotmail.com Antwort an: Yanchang Zhao zhaoyanchang@hotmail.com An: AISWORLD Information Systems World Network isworld@lyris.isworld.org
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New book release
Post-Mining of Association Rules: Techniques for Effective Knowledge Extraction
ISBN: 978-1-60566-404-0; 394 pp; May 2009
Edited by: Yanchang Zhao, Chengqi Zhang, and Longbing Cao
University of Technology, Sydney, Australia
Published under the imprint Information Science Reference
(formerly Idea Group Reference)
http://www.igi-global.com/reference/details.asp?ID=33406
http://www-staff.it.uts.edu.au/~yczhao/book-PMAR.htm
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DESCRIPTION
There is often a large number of association rules discovered
in data mining practice, making it difficult for users to
identify those that are of particular interest to them.
Therefore, it is important to remove insignificant rules and
prune redundancy as well as summarize, visualize, and
post-mine the discovered rules.
Post-Mining of Association Rules: Techniques for Effective
Knowledge Extraction provides a systematic collection on
post-mining, summarization and presentation of association
rules, and new forms of association rules. This book presents
researchers, practitioners, and academicians with tools to
extract useful and actionable knowledge after discovering
a large number of association rules.
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"This book examines the post-analysis and post-mining of
association rules to find useful knowledge from a large
number of discovered rules and presents a systematic view
of the above topic."
- Yanchang Zhao, University of Technology Sydney, Australia
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TOPICS COVERED
Association rules
Background knowledge for association
Classification results analyses
Data stream management system
Maintenance of association rules
Meta-knowledge based approach
New forms of association rules
Post-mining of association rules
Semantics-based classification
Variations on associative classifiers
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For more information about Post-Mining of Association Rules:
Techniques for Effective Knowledge Extraction, you can view
the title information sheet at
http://www.igi-global.com/downloads/pdf/33406.pdf.
To view the Table of Contents and a complete list of
contributors online go to
http://www.igi-global.com/reference/details.asp?ID=33406&v=tableOfConten....
You can also view the first chapter of the publication at
http://www.igi-global.com/downloads/excerpts/33406.pdf.
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ABOUT THE EDITORS
Yanchang Zhao is a Postdoctoral Research Fellow in Data
Sciences & Knowledge Discovery Research Lab, Centre for
Quantum Computation and Intelligent Systems, Faculty of
Engineering & IT, University of Technology, Sydney, Australia.
His research interests focus on association rules, sequential
patterns, clustering and post-mining. He has published more
than 30 papers on the above topics, including six journal
articles and two book chapters. He served as a chair of two
international workshops, and a program committee member for
11 international conferences and a reviewer for 8
international journals and over a dozen of international
conferences.
Chengqi Zhang is a Research Professor in Faculty of
Engineering & IT, University of Technology, Sydney, Australia.
He is the director of the Director of UTS Research Centre for
Quantum Computation and Intelligent Systems and a Chief
Investigator in Data Mining Program for Australian Capital
Markets on Cooperative Research Centre. He has been a chief
investigator of eight research projects. His research
interests include Data Mining and Multi-Agent Systems.
He is a co-author of three monographs, a co-editor of nine
books, and an author or co-author of more than 150 research
papers. He is the chair of the ACS (Australian Computer
Society) National Committee for Artificial Intelligence and
Expert Systems, a chair/member of the Steering Committee for
three international conference.
Longbing Cao is an Associate Professor in Faculty of
Engineering & IT, University of Technology, Sydney (Australia).
He is the Director of Data Sciences & Knowledge Discovery
Research Lab. His research interest focuses on domain driven
data mining, multi-agents, and the integration of agent and
data mining. He is a chief investigator of two ARC (Australian
Research Council) Discovery projects and one ARC Linkage
project. He has over 50 publications, including one monograph,
two edited books and 10 journal articles. He is a program
co-chair of 11 international conferences.
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To view the full contents of this publication, check for
Post-Mining of Association Rules: Techniques for Effective
Knowledge Extraction in your institution’s library. If your
library does not currently own this title, please recommend
it to your librarian.
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