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📚 Knowledge Graphs ✨This book provides a comprehensive and accessible introduction to knowledge graphs, which have recently
📚 Knowledge GraphsThis book provides a comprehensive and accessible introduction to knowledge graphs, which have recently garnered notable attention from both industry and academia. Knowledge graphs are founded on the principle of applying a graph-based abstraction to data, and are now broadly deployed in scenarios that require integrating and extracting value from multiple, diverse sources of data at large scale. 🧑‍💼 authors: Aidan Hogan, Eva Blomqvist, Michael Cochez, Claudia D'Amato, Gerard de Melo, Claudio Gutierrez, Sabrina Kirrane, Jose Emilio Labra Gayo, Roberto Navigli, Sebastian Neumaier, Axel-Cyrille Ngonga Ngomo, Axel Polleres, Sabbir M Rashid, Anisa Rula, Juan Sequeda, Lukas Schmelzeisen, Steffen Staab, Antoine Zimmerman 🗓Publish year: 2021 📎Study 📲Channel: @ComplexNetworkAnalysis #Book #graph #Data_Graphs #Graph_Algorithms #Graph_Analytics #Graph_Neural_Networks #Knowledge_Graphs #Social_Networks

📄Complex systems and network science: a survey 📘 journal: Journal of Systems Engineering and Electronics (I.F=2.1) 🗓Publis
📄Complex systems and network science: a survey 📘 journal: Journal of Systems Engineering and Electronics (I.F=2.1) 🗓Publish year: 2023 📎Study paper 📱Channel: @ComplexNetworkAnalysis #paper #Complex_systems #network_science #survey

📄Machine Learning for Anomaly Detection: A Systematic Review 📘 journal: IEEE Access(I.F=3.9) 🗓Publish year: 2021 📎Study p
📄Machine Learning for Anomaly Detection: A Systematic Review 📘 journal: IEEE Access(I.F=3.9) 🗓Publish year: 2021 📎Study paper 📱Channel: @ComplexNetworkAnalysis #paper #Machine_Learning #Anomaly_Detection #Review

📚Graph Theory Notes 🧑‍💼 author: Vadim Lozin in Institute of Mathematics University of Warwick 📎Study 📲Channel: @ComplexN
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📚Graph Theory Notes 🧑‍💼 author: Vadim Lozin in Institute of Mathematics University of Warwick 📎Study 📲Channel: @ComplexNetworkAnalysis #Booklet #graph

📄Spatial social network research: a bibliometric analysis 📘 journal: Computational Urban Science 🗓Publish year: 2022 📎Stu
📄Spatial social network research: a bibliometric analysis 📘 journal: Computational Urban Science 🗓Publish year: 2022 📎Study paper 📱Channel: @ComplexNetworkAnalysis #paper #Spatial #research #bibliometric

📄Spatial social network research: a bibliometric analysis 📘 journal: Computational Urban Science 🗓Publish year: 2022 📎Stu
📄Spatial social network research: a bibliometric analysis 📘 journal: Computational Urban Science 🗓Publish year: 2022 📎Study paper 📱Channel: @ComplexNetworkAnalysis #paper #Spatial #research #bibliometric

📄Information cascades in complex networks 📘 journal: Journal of Complex Networks (I.F=1.492) 🗓Publish year: 2017 📎Study p
📄Information cascades in complex networks 📘 journal: Journal of Complex Networks (I.F=1.492) 🗓Publish year: 2017 📎Study paper 📲Channel: @ComplexNetworkAnalysis #paper #graph #cascades #review

📄 Survey of Deep Graph Clustering: Taxonomy,Challenge, Application, and Open Resource 🗓Publish year: 2023 📎Study paper 📱C
📄 Survey of Deep Graph Clustering: Taxonomy,Challenge, Application, and Open Resource 🗓Publish year: 2023 📎Study paper 📱Channel: @ComplexNetworkAnalysis #paper #Deep #Graph #Clustering #Taxonomy #Challenge #Application #Open_Resource #survey

📄Machine Learning for Anomaly Detection: A Systematic Review 📘 journal: IEEE Acess (I.F=3.476) 🗓Publish year: 2021 📎Study
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📄Machine Learning for Anomaly Detection: A Systematic Review 📘 journal: IEEE Acess (I.F=3.476) 🗓Publish year: 2021 📎Study paper 📲Channel: @ComplexNetworkAnalysis #paper #graph #Anomaly_detection #review

📄A Survey on Graph Counterfactual Explanations: Definitions, Methods, Evaluation, and Research Challenges 📘 journal: ACM Co
📄A Survey on Graph Counterfactual Explanations: Definitions, Methods, Evaluation, and Research Challenges 📘 journal: ACM Computing Surveys (I.F=16.6) 🗓Publish year: 2023 📎Study paper 📱Channel: @ComplexNetworkAnalysis #paper #Graph #Counterfactual #Explanations #Evaluation #Challenges #survey

📄 A Survey on Graph Neural Networks for Time Series: Forecasting, Classification, Imputation, and Anomaly Detection 🗓Publis
📄 A Survey on Graph Neural Networks for Time Series: Forecasting, Classification, Imputation, and Anomaly Detection 🗓Publish year: 2023 📎Study paper 📲Channel: @ComplexNetworkAnalysis #paper #survey #GNN #anomaly_detection #time_series

📄Privacy-Preserving Graph Machine Learning from Data to Computation: A Survey 🗓Publish year: 2023 📎Study paper 📱Channel:
📄Privacy-Preserving Graph Machine Learning from Data to Computation: A Survey 🗓Publish year: 2023 📎Study paper 📱Channel: @ComplexNetworkAnalysis #paper #Privacy #Preserving #Graph_Machine_Learning #Computation #survey

📄Influence maximization in social networks: a survey of behaviour-aware methods 📘 journal: Social Network Analysis and Mini
📄Influence maximization in social networks: a survey of behaviour-aware methods 📘 journal: Social Network Analysis and Mining (SNAM) (I.F=2.8) 🗓Publish year: 2023 📎Study paper 📱Channel: @ComplexNetworkAnalysis #paper #Influence #maximization #behaviour_aware #survey

📄 A comprehensive survey of personal knowledge graphs 📘 journal: wiley(I.F=13.3) 🗓Publish year: 2023 📎 Study the paper 📲Channel: @ComplexNetworkAnalysis #paper #survey #knowledge_graphs

📄The Use of Graph Theory for Modeling and Analyzing the Structure of a Complex System, with the Example of an Industrial Gra
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📄The Use of Graph Theory for Modeling and Analyzing the Structure of a Complex System, with the Example of an Industrial Grain Drying Line 📘 journal: processes (I.F=3.352) 🗓Publish year: 2023 📎Study paper 📲Channel: @ComplexNetworkAnalysis #paper #graph #analyis #Industrial_Grain_Drying_Line

📄Community Detection Algorithms in Healthcare Applications: A Systematic Review 📘 journal: IEEE Access (I.F=3.9) 🗓Publish
📄Community Detection Algorithms in Healthcare Applications: A Systematic Review 📘 journal: IEEE Access (I.F=3.9) 🗓Publish year: 2023 📎Study paper 📱Channel: @ComplexNetworkAnalysis #paper #Community_Detection #Healthcare #Applications #review

📄Graph Convolutional Networks: Introduction to GNNs 💥Technical paper 🌐 Study 📲Channel: @ComplexNetworkAnalysis #paper #Graph #GNN

📄Graph Theory 🧑🏻‍💼 author : Marc Lackenby 📎 Study the paper 📲Channel: @ComplexNetworkAnalysis #paper #graph
📄Graph Theory 🧑🏻‍💼 author : Marc Lackenby 📎 Study the paper 📲Channel: @ComplexNetworkAnalysis #paper #graph

📄Graph Data Structure And Algorithms 💥Technical paper 🌐 Study 📲Channel: @ComplexNetworkAnalysis #paper #Graph #Data_Structure #Algorithms