Overview
- 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
Part of the book series: Lecture Notes in Social Networks (LNSN)
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Keywords
Table of contents (11 chapters)
Editors and Affiliations
About the editors
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 NetworksAnalysis 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.
Bibliographic Information
Book Title: Machine Learning Techniques for Online Social Networks
Editors: Tansel Özyer, Reda Alhajj
Series Title: Lecture Notes in Social Networks
DOI: https://doi.org/10.1007/978-3-319-89932-9
Publisher: Springer Cham
eBook Packages: Social Sciences, Social Sciences (R0)
Copyright Information: Springer International Publishing AG, part of Springer Nature 2018
Hardcover ISBN: 978-3-319-89931-2Published: 31 May 2018
Softcover ISBN: 978-3-030-07896-6Published: 14 December 2018
eBook ISBN: 978-3-319-89932-9Published: 30 May 2018
Series ISSN: 2190-5428
Series E-ISSN: 2190-5436
Edition Number: 1
Number of Pages: VIII, 236
Number of Illustrations: 17 b/w illustrations, 85 illustrations in colour
Topics: Computational Social Sciences, Data Mining and Knowledge Discovery, Social Media, Artificial Intelligence