Cover Image
Read Now

Machine Learning Techniques for Online Social Networks

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...

Full description

Bibliographic Details
Other Authors: Özyer, Tansel (Editor), Alhajj, Reda (Editor)
Format: eBook
Language:English
Published: Cham Springer International Publishing 2018, 2018
Edition:1st ed. 2018
Series:Lecture Notes in Social Networks
Subjects:
Sociology / Methodology
Social Media
Artificial Intelligence
Data Mining
Data Mining And Knowledge Discovery
Sociological Methods
Online Access:
Collection: Springer eBooks 2005- - Collection details see MPG.ReNa
LEADER 02668nmm a2200361 u 4500
001 EB001824226
003 EBX01000000000000000990672
005 00000000000000.0
007 cr|||||||||||||||||||||
008 180604 ||| eng
020 |a 9783319899329 
100 1 |a Özyer, Tansel  |e [editor] 
245 0 0 |a Machine Learning Techniques for Online Social Networks  |h Elektronische Ressource  |c edited by Tansel Özyer, Reda Alhajj 
250 |a 1st ed. 2018 
260 |a Cham  |b Springer International Publishing  |c 2018, 2018 
300 |a VIII, 236 p. 102 illus., 85 illus. in color  |b online resource 
505 0 |a Chapter1. Acceleration of Functional Cluster Extraction and Analysis of Cluster Affinity -- Chapter2. Delta-Hyperbolicity and the Core-Periphery Structure in Graphs -- Chapter3. A Framework for OSN Performance Evaluation Studies -- Chapter4. On The Problem of Multi-Staged Impression Allocation in Online Social Networks -- Chapter5. Order-of-Magnitude Popularity Estimation of Pirated Content -- Chapter6. Learning What to Share in Online Social Networks using Deep Reinforcement Learning -- Chapter7. Centrality and Community Scoring Functions in Incomplete Networks: Their Sensitivity, Robustness and Reliability -- Chapter8. Ameliorating Search Results Recommendation System based on K-means Clustering Algorithm and Distance Measurements -- Chapter9. Dynamics of large scale networks following a merger -- Chapter10. Cloud Assisted Personal Online Social Network -- Chapter11. Text-Based Analysis of Emotion by Considering Tweets 
653 |a Sociology / Methodology 
653 |a Social media 
653 |a Artificial Intelligence 
653 |a Data mining 
653 |a Social Media 
653 |a Artificial intelligence 
653 |a Data Mining and Knowledge Discovery 
653 |a Sociological Methods 
700 1 |a Alhajj, Reda  |e [editor] 
041 0 7 |a eng  |2 ISO 639-2 
989 |b Springer  |a Springer eBooks 2005- 
490 0 |a Lecture Notes in Social Networks 
028 5 0 |a 10.1007/978-3-319-89932-9 
856 4 0 |u https://doi.org/10.1007/978-3-319-89932-9?nosfx=y  |x Verlag  |3 Volltext 
082 0 |a 301.01 
520 |a 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. 

Similar Items