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Machine Learning Techniques for Online Social Networks

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Cover of 'Machine Learning Techniques for Online Social Networks'

Table of Contents

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    Book Overview
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    Chapter 1 Acceleration of Functional Cluster Extraction and Analysis of Cluster Affinity
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    Chapter 2 δ -Hyperbolicity and the Core-Periphery Structure in Graphs
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    Chapter 3 A Framework for OSN Performance Evaluation Studies
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    Chapter 4 On the Problem of Multi-Staged Impression Allocation in Online Social Networks
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    Chapter 5 Order-of-Magnitude Popularity Estimation of Pirated Content
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    Chapter 6 Learning What to Share in Online Social Networks Using Deep Reinforcement Learning
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    Chapter 7 Centrality and Community Scoring Functions in Incomplete Networks: Their Sensitivity, Robustness, and Reliability
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    Chapter 8 Ameliorating Search Results Recommendation System Based on K -Means Clustering Algorithm and Distance Measurements
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    Chapter 9 Dynamics of Large-Scale Networks Following a Merger
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    Chapter 10 Cloud Assisted Personal Online Social Network
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    Chapter 11 Text-Based Analysis of Emotion by Considering Tweets
Attention for Chapter 4: On the Problem of Multi-Staged Impression Allocation in Online Social Networks
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Chapter title
On the Problem of Multi-Staged Impression Allocation in Online Social Networks
Chapter number 4
Book title
Machine Learning Techniques for Online Social Networks
Published by
Springer, Cham, January 2018
DOI 10.1007/978-3-319-89932-9_4
Book ISBNs
978-3-31-989931-2, 978-3-31-989932-9
Authors

Inzamam Rahaman, Patrick Hosein, Rahaman, Inzamam, Hosein, Patrick

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