Data Mining for Social Network Data (Paperback, 2010)

Driven by counter-terrorism efforts, marketing analysis and an explosion in online social networking in recent years, data mining has moved to the forefront of information science. This proposed Special Issue on Data Mining for Social Network Data will present a broad range of recent studies in social networking analysis. It will focus on emerging trends and needs in discovery and analysis of communities, solitary and social activities, activities in open for a and commercial sites as well. It will also look at network modeling, infrastructure construction, dynamic growth and evolution pattern discovery using machine learning approaches and multi-agent based simulations. Editors are three rising stars in world of data mining, knowledge discovery, social network analysis, and information infrastructures, and are anchored by Springer author/editor Hsinchun Chen (Terrorism Informatics; Medical Informatics; Digital Government), who is one of the most prominent intelligence analysis and data mining experts in the world.

General

Imprint:	Springer-Verlag New York
Country of origin:	United States
Series:	Annals of Information Systems, 12
Release date:	July 2010
First published:	2010
Editors:	Nasrullah Memon • Jennifer Jie Xu • David L. Hicks • Hsinchun Chen
Dimensions:	235 x 155 x 17mm (L x W x T)
Format:	Paperback
Pages:	216
Edition:	2010
ISBN-13:	978-1-4419-6286-7
Categories:	Books > Social sciences > General Books > Computing & IT > Applications of computing > Pattern recognition Books > Business & Economics > Business & management > Business mathematics & systems > General
LSN:	1-4419-6286-7
Barcode:	9781441962867

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