Machine Learning in Social Networks

Manasvi Aggarwal|M.N. Murty

ISBN 10: 9813340215 / ISBN 13: 9789813340213

Edité par Springer Singapore, 2020

A propos de cet article

Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Highlights the understanding of complex systems in different domains including health, education, agriculture,&nbspand transportationCombines both&nbspconventional machine learning (ML) and deep learning (DL) techniques to understand com.

N° de réf. du vendeur 449943281

Détails bibliographiques

• Titre: Machine Learning in Social Networks
• Éditeur: Springer Singapore
• Date de parution: 2020
• Langue: anglais
• ISBN à 10 chiffres: 9813340215
• ISBN à 13 chiffres: 9789813340213
• Reliure: Kartoniert / Broschiert
• État de l'article: New

A propos de ce titre

Synopsis

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 protein–protein 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 ofcurrent 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. 

À propos de l?auteur

M.N. Murty is currently a Professor in the Department of Computer Science and Automation at the Indian Institute of Science, Bangalore. His research interests are in the area of pattern recognition, data mining, and social network analysis.

Ms. Manasvi Aggarwal is currently pursuing her M.S. at the Indian Institute of Science, Bangalore. Her research interest is in the areas of social networks and machine learning