Machine Learning Techniques for Online Social Networks

This book PDF is perfect for those who love Social Science genre, written by Tansel Özyer and published by Springer which was released on 30 May 2018 with total hardcover pages 236. You could read this book directly on your devices with pdf, epub and kindle format, check detail and related Machine Learning Techniques for Online Social Networks books below.

Machine Learning Techniques for Online Social Networks

Author	: Tansel Özyer
File Size	: 46,8 Mb
Publisher	: Springer
Language	: English
Release Date	: 30 May 2018
ISBN	: 9783319899329
Pages	: 236 pages

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Machine Learning Techniques for Online Social Networks by Tansel Özyer Book PDF Summary

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.

Machine Learning Techniques for Online Social Networks by Tansel Özyer,Reda Alhajj

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Online Social Networks Security by Brij B. Gupta,Somya Ranjan Sahoo

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Artificial neural networks (ANNs) present many benefits in analyzing complex data in a proficient manner. As an effective and efficient problem-solving method, ANNs are incredibly useful in many different fields. From education to medicine and banking to engineering, artificial neural networks are a growing phenomenon as more realize the plethora

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The Influence of Technology on Social Network Analysis and Mining by Tansel Özyer,Jon Rokne,Gerhard Wagner,Arno H.P. Reuser

The study of social networks was originated in social and business communities. In recent years, social network research has advanced significantly; the development of sophisticated techniques for Social Network Analysis and Mining (SNAM) has been highly influenced by the online social Web sites, email logs, phone logs and instant messaging

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