Applied data mining

Xu, G; Zong, Y; Yang, Z

Applied data mining

Xu, G

Zong, Y Yang, Z

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Publication Type:: Book
Citation:: 2013, pp. 1 - 271
Issue Date:: 2013-01-01

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Field	Value	Language
dc.contributor.author	Xu, G https://orcid.org/0000-0003-4493-6663	en_US
dc.contributor.author	Zong, Y	en_US
dc.contributor.author	Yang, Z	en_US
dc.date.issued	2013-01-01	en_US
dc.identifier.citation	2013, pp. 1 - 271	en_US
dc.identifier.isbn	9781466585836	en_US
dc.identifier.uri	http://hdl.handle.net/10453/31006
dc.description.abstract	© 2013 by Taylor & Francis Group, LLC. Data mining has witnessed substantial advances in recent decades. New research questions and practical challenges have arisen from emerging areas and applications within the various fields closely related to human daily life, e.g. social media and social networking. This book aims to bridge the gap between traditional data mining and the latest adv.	en_US
dc.title	Applied data mining	en_US
dc.type	Book
utslib.for	0801 Artificial Intelligence and Image Processing	en_US
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Computer Science
pubs.organisational-group	/University of Technology Sydney/Strength - AAI - Advanced Analytics Institute Research Centre
utslib.copyright.status	closed_access
pubs.publication-status	Published	en_US

Abstract:

© 2013 by Taylor & Francis Group, LLC. Data mining has witnessed substantial advances in recent decades. New research questions and practical challenges have arisen from emerging areas and applications within the various fields closely related to human daily life, e.g. social media and social networking. This book aims to bridge the gap between traditional data mining and the latest adv.

Please use this identifier to cite or link to this item:

http://hdl.handle.net/10453/31006