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Advances in social network mining and analysis : second international workshop, SNAKDD 2008, Las Vegas, NV, USA, August 24-27, 2008 : revised selected papers / Lee Giles [and others] (eds.).

By: Contributor(s): Material type: TextTextSeries: Lecture notes in computer science ; 5498. | LNCS sublibrary. SL 1, Theoretical computer science and general issues.Publication details: Berlin : Springer, 2010.Description: 1 online resource (x, 130 pages) : illustrationsContent type:
  • text
Media type:
  • computer
Carrier type:
  • online resource
ISBN:
  • 9783642149290
  • 3642149294
Other title:
  • SNAKDD 2008
  • KDD 2008
Subject(s): Genre/Form: Additional physical formats: Print version:: Advances in social network mining and analysis.DDC classification:
  • 006.3/12 22
LOC classification:
  • ZA4235 .I58 2010
NLM classification:
  • ZA 4235
Online resources:
Contents:
Leveraging Label-Independent Features for Classification in Sparsely Labeled Networks: An Empirical Study -- Community Detection Using a Measure of Global Influence -- Communication Dynamics of Blog Networks -- Finding Spread Blockers in Dynamic Networks -- Social Network Mining with Nonparametric Relational Models -- Using Friendship Ties and Family Circles for Link Prediction -- Information Theoretic Criteria for Community Detection.
Summary: Annotation This work constitutes the proceedings of the Second International Workshop on Advances in Social Network and Analysis, held in Las Vegas, NV, USA in August 2008.
Holdings
Item type Current library Collection Call number Status Date due Barcode Item holds
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Total holds: 0

" ... co-locates with the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD)"--Preface

Includes bibliographical references and index.

Annotation This work constitutes the proceedings of the Second International Workshop on Advances in Social Network and Analysis, held in Las Vegas, NV, USA in August 2008.

Print version record.

Leveraging Label-Independent Features for Classification in Sparsely Labeled Networks: An Empirical Study -- Community Detection Using a Measure of Global Influence -- Communication Dynamics of Blog Networks -- Finding Spread Blockers in Dynamic Networks -- Social Network Mining with Nonparametric Relational Models -- Using Friendship Ties and Family Circles for Link Prediction -- Information Theoretic Criteria for Community Detection.

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