Post-mining of association rules: Techniques for effective knowledge extraction

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dc.contributor.author Zhao, Y
dc.contributor.author Zhang, C
dc.contributor.author Cao, L
dc.date.accessioned 2010-07-13T08:46:47Z
dc.date.issued 2009
dc.identifier.citation 2009, pp. 1 - 372
dc.identifier.isbn 9781605664040
dc.identifier.other B1 en_US
dc.identifier.uri http://hdl.handle.net/10453/12438
dc.description.abstract 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. © 2009 by IGI Global. All rights reserved.
dc.publisher IGI Global
dc.relation.isbasedon 10.4018/978-1-60566-404-0
dc.title Post-mining of association rules: Techniques for effective knowledge extraction
dc.type Chapter
dc.journal.number en_US
dc.publocation USA en_US
dc.identifier.startpage 1 en_US
dc.identifier.endpage 10 en_US
dc.cauo.name FEIT.School of Systems, Management and Leadership en_US
dc.conference Verified OK en_US
dc.for 120402 Engineering Design Knowledge
dc.personcode 998488
dc.percentage 100 en_US
dc.classification.name Engineering Design Knowledge en_US
dc.classification.type FOR-08 en_US
dc.edition 1 en_US
dc.custom en_US
dc.date.activity en_US
dc.location.activity en_US
dc.description.keywords NA en_US
pubs.embargo.period Not known
pubs.organisational-group /University of Technology Sydney
utslib.copyright.status Closed Access
utslib.copyright.date 2015-04-15 12:17:09.805752+10


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