Özyer, Tansel Alhajj, Reda2020-01-282020-01-282018Özyer, T., and Alhajj, R. (Eds.). (2018). Machine Learning Techniques for Online Social Networks. Springer.978-3-319-89932-9978-3-319-89931-2https://www.springer.com/gp/book/9783319899312https://hdl.handle.net/20.500.11851/3303[Pages 1-22] Acceleration of Functional Cluster Extraction and Analysis of Cluster Affinity [Pages 23-43] -Hyperbolicity and the Core-Periphery Structure in Graphs [Pages 45-64] A Framework for OSN Performance Evaluation Studies [Pages 65-84] On the Problem of Multi-Staged Impression Allocation in Online Social Networks [Pages 85-113] Order-of-Magnitude Popularity Estimation of Pirated Content [Pages 115-133] Learning What to Share in Online Social Networks Using Deep Reinforcement Learning [Pages 135-154] Centrality and Community Scoring Functions in Incomplete Networks: Their Sensitivity, Robustness, and Reliability [Pages 155-172] Ameliorating Search Results Recommendation System Based on K-Means Clustering Algorithm and Distance Measurements [Pages 173-193] Dynamics of Large-Scale Networks Following a Merger [Pages 195-218] Cloud Assisted Personal Online Social Network [Pages 219-236] Text-Based Analysis of Emotion by Considering Tweetseninfo:eu-repo/semantics/closedAccessComputer scienceartificial intelligenceinformation systemsinterdisciplinary applicationsBook10.1007/978-3-319-89932-9