Network Analysis Resources & Updates

📘 Machine Learning in Complex Networks 📝Authors: Thiago Christiano Silva, Liang Zhao 📅Publish year: 2016 💥This book presents the features and advantages offered by complex networks in the machine learning domain. In the first part, an overview on complex networks and network-based machine learning is presented, offering necessary background material. In the second part, we describe in details some specific techniques based on complex networks for supervised, non-supervised, and semi-supervised learning. Particularly, a stochastic particle competition technique for both non-supervised and semi-supervised learning using a stochastic nonlinear dynamical system is described in details. Moreover, an analytical analysis is supplied, which enables one to predict the behavior of the proposed technique. In addition, data reliability issues are explored in semi-supervised learning. 📎 Study the book 📲Channel: @ComplexNetworkAnalysis #book #Machine_Learning

📄Estimating Complex Networks Centrality via neural networks and machine learning 📘Conference : 2015 International Joint Conference on Neural Networks (IJCNN) 🗓Publish year: 2015 📎Study paper 📲Channel: @ComplexNetworkAnalysis #paper #Machine_Learning

📄Finding key players in complex networks through deep reinforcement learning 📘Journal: Nature Machine Intelligence (I.F=25.9) 🗓Publish year: 2021 📎Study paper 📲Channel: @ComplexNetworkAnalysis #paper #deep_reinforcement_learning

📄New research methods & algorithms in social network analysis 📘Journal: Future Generation Computer Systems (I.F=8.872 ) 🗓Publish year: 2021 📎Study paper 📲Channel: @ComplexNetworkAnalysis #paper #social_network

📄A Systematic Survey of Opinion Leader in Online Social Network 📘Conference: 2018 International Conference on Soft-computing and Network Security (ICSNS) 🗓Publish year: 2018 📎Study paper 📲Channel: @ComplexNetworkAnalysis #paper #Survey