Machine learning in social networks : embedding nodes, edges, communities, and graphs / Manasvi Aggarwal, M.N. Murty.
Aggarwal, Manasvi, author.; Murty, M. Narasimha, author.
2021
Q325.5
Available Online

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Title Machine learning in social networks : embedding nodes, edges, communities, and graphs / Manasvi Aggarwal, M.N. Murty.
Author Aggarwal, Manasvi, author.
ISBN 9789813340220 (electronic bk.)
9813340223 (electronic bk.)
9789813340213
9813340215
DOI https://doi.org/10.1007/978-981-33-4022-0
Published Singapore : Springer, [2021]
Language English
Description 1 online resource (xi, 112 pages) : illustrations (color, black and white)
Other Standard Identifiers 10.1007/978-981-33-4022-0 doi
Call Number Q325.5
Dewey Decimal Classification 006.3/1
Summary This book deals with network representation learning. It deals with embedding nodes, edges, subgraphs and graphs. There is a growing interest in understanding complex systems in different domains including health, education, agriculture and transportation. Such complex systems are analyzed by modeling, using networks that are aptly called complex networks. Networks are becoming ubiquitous as they can represent many real-world relational data, for instance, information networks, molecular structures, telecommunication networks and proteinprotein interaction networks. Analysis of these networks provides advantages in many fields such as recommendation (recommending friends in a social network), biological field (deducing connections between proteins for treating new diseases) and community detection (grouping users of a social network according to their interests) by leveraging the latent information of networks. An active and important area of current interest is to come out with algorithms that learn features by embedding nodes or (sub)graphs into a vector space. These tasks come under the broad umbrella of representation learning. A representation learning model learns a mapping function that transforms the graphs' structure information to a low-/high-dimension vector space maintaining all the relevant properties.
Bibliography, etc. Note Includes bibliographical references and index.
Access Note Access limited to authorized users.
Digital File Characteristics text file
PDF
Source of Description Online resource; title from PDF title page (SpringerLink, viewed February 2, 2021).
Added Author Murty, M. Narasimha, author.
Series SpringerBriefs in applied sciences and technology. Computational intelligence. 2625-3704
Available in Other Form Machine learning in social networks.
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Record Appears in Online Resources > Ebooks
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Introduction
Representations of Networks
Deep Learning
Node Representations
Embedding Graphs
Conclusions.

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