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Machine Learning Techniques for Online Social Networks (Lecture Notes in Social Networks)

Machine Learning Techniques for Online Social Networks (Lecture Notes in Social Networks)

by Tansel Özyer (Editor), Reda Alhajj (Editor)

  • New

    Hardcover 2018

    $122.48
Synopsis

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.

$122.48

Quantity

20+ in stock

More Information

Format: Hardcover
 Pages: 246
 Edition: 1st ed. 2018
 Publisher: Springer
Published: 31 May 2018
ISBN 10: 3319899317
ISBN 13: 9783319899312

Author Bio
Tansel OEzyer 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.