Lecture Notes in Social Networks

Machine Learning Techniques for Online Social Networks

Editors: Özyer, Tansel, Alhajj, Reda (Eds.)

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  • Editors are widely known and well established scholars in social network analysis 
  • Covers the link between machine learning techniques and social networks
  • Contains case studies describing how various domains may benefit from online social networks
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eBook 74,96 €
price for Spain (gross)
  • ISBN 978-3-319-89932-9
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  • Immediate eBook download after purchase
Hardcover 93,59 €
price for Spain (gross)
  • ISBN 978-3-319-89931-2
  • Free shipping for individuals worldwide
  • Usually dispatched within 3 to 5 business days.
  • The final prices may differ from the prices shown due to specifics of VAT rules
About this book

The book covers tools in the study of online social networks such as machine learning techniques, clustering, and deep learning. A variety of theoretical aspects, application domains, and case studies for analyzing social network data are covered. The aim is to provide new perspectives on utilizing machine learning and related scientific methods and techniques for social network analysis. Machine Learning Techniques for Online Social Networks will appeal to researchers and students in these fields. 

About the authors

Tansel Özyer is an associate professor of Computer Engineering at TOBB University of Economics and Technology, Turkey. He completed his PhD in Computer Science, University of Calgary. He received his MSc and BSc from Computer Engineering departments of METU and Bilkent University. Research interests are data mining, social network analysis, machine learning, bioinformatics, XML, mobile databases, and computer vision.
Reda Alhajj is a professor in the Department of Computer Science at the University of Calgary. He published over 500 papers in refereed international journals and conferences. He is founding editor in chief of the Springer premier journal “Social Networks Analysis and Mining”, founding editor-in-chief of Springer Series “Lecture Notes on Social Networks”, founding editor-in-chief of Springer journal “Network Modeling Analysis in Health Informatics and Bioinformatics”, founding co-editor-in-chief of Springer “Encyclopedia on Social Networks Analysis and Mining”, founding steering chair of IEEE/ACM ASONAM, and three accompanying symposiums FAB, FOSINT-SI and HI-BI-BI. Dr. Alhajj's research concentrates primarily on data science from management to integration and analysis.

Table of contents (11 chapters)

  • Acceleration of Functional Cluster Extraction and Analysis of Cluster Affinity

    Fushimi, Takayasu (et al.)

    Pages 1-22

  • δ-Hyperbolicity and the Core-Periphery Structure in Graphs

    Alrasheed, Hend

    Pages 23-43

  • A Framework for OSN Performance Evaluation Studies

    Terevinto, Pablo Nicolás (et al.)

    Pages 45-64

  • On the Problem of Multi-Staged Impression Allocation in Online Social Networks

    Rahaman, Inzamam (et al.)

    Pages 65-84

  • Order-of-Magnitude Popularity Estimation of Pirated Content

    Chelmis, Charalampos (et al.)

    Pages 85-113

Buy this book

eBook 74,96 €
price for Spain (gross)
  • ISBN 978-3-319-89932-9
  • Digitally watermarked, DRM-free
  • Included format: PDF, EPUB
  • ebooks can be used on all reading devices
  • Immediate eBook download after purchase
Hardcover 93,59 €
price for Spain (gross)
  • ISBN 978-3-319-89931-2
  • Free shipping for individuals worldwide
  • Usually dispatched within 3 to 5 business days.
  • The final prices may differ from the prices shown due to specifics of VAT rules
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Bibliographic Information

Bibliographic Information
Book Title
Machine Learning Techniques for Online Social Networks
Editors
  • Tansel Özyer
  • Reda Alhajj
Series Title
Lecture Notes in Social Networks
Copyright
2018
Publisher
Springer International Publishing
Copyright Holder
Springer International Publishing AG, part of Springer Nature
eBook ISBN
978-3-319-89932-9
DOI
10.1007/978-3-319-89932-9
Hardcover ISBN
978-3-319-89931-2
Series ISSN
2190-5428
Edition Number
1
Number of Pages
VIII, 236
Number of Illustrations
17 b/w illustrations, 85 illustrations in colour
Topics