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Mining and Analyzing Social Networks [electronic resource] / edited by I-Hsien Ting, Hui-Ju Wu, Tien-Hwa Ho.

By: Contributor(s): Material type: TextTextSeries: Studies in Computational Intelligence ; 288Publisher: Berlin, Heidelberg : Springer Berlin Heidelberg, 2010Description: 200p. 39 illus. in color. online resourceContent type:
  • text
Media type:
  • computer
Carrier type:
  • online resource
ISBN:
  • 9783642134227
Subject(s): Additional physical formats: Printed edition:: No titleDDC classification:
  • 006.3 23
LOC classification:
  • Q342
Online resources:
Contents:
Graph Model for Pattern Recognition in Text -- Retrieving Wiki Content Using an Ontology -- Ego-Centric Network Sampling in Viral Marketing Applications -- Integrating SNA and DM Technology into HR Practice and Research: Layoff Prediction Model -- Actor Identification in Implicit Relational Data Sources -- Perception of Online Social Networks -- Ranking Learning Entities on the Web by Integrating Network-Based Features -- Discovering Proximal Social Intelligence for Quality Decision Support -- Discovering User Interests by Document Classification -- Network Analysis of Opto-Electronics Industry Cluster: A Case of Taiwan.
In: Springer eBooksSummary: This book will focus upon Mining and Analyzing social network. Some chapters in this book are extended from the papers that pre-sented in MSNDS2009 (the First International Workshop on Mining Social Networks for Decision Support) and SNMABA2009 ((The International Workshop on Social Networks Mining and Analysis for Business Applications)). In addition, we also sent invitations to researchers that are famous in this research area to contribute for this book.
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Item type Current library Call number Status Date due Barcode
E-Book E-Book Central Library Available E-46814

Graph Model for Pattern Recognition in Text -- Retrieving Wiki Content Using an Ontology -- Ego-Centric Network Sampling in Viral Marketing Applications -- Integrating SNA and DM Technology into HR Practice and Research: Layoff Prediction Model -- Actor Identification in Implicit Relational Data Sources -- Perception of Online Social Networks -- Ranking Learning Entities on the Web by Integrating Network-Based Features -- Discovering Proximal Social Intelligence for Quality Decision Support -- Discovering User Interests by Document Classification -- Network Analysis of Opto-Electronics Industry Cluster: A Case of Taiwan.

This book will focus upon Mining and Analyzing social network. Some chapters in this book are extended from the papers that pre-sented in MSNDS2009 (the First International Workshop on Mining Social Networks for Decision Support) and SNMABA2009 ((The International Workshop on Social Networks Mining and Analysis for Business Applications)). In addition, we also sent invitations to researchers that are famous in this research area to contribute for this book.

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