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Архив постов
📚 Knowledge Graphs
✨This 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
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📲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)
🗓Publish year: 2023
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📱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
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📱Channel: @ComplexNetworkAnalysis
#paper #Machine_Learning #Anomaly_Detection #Review
+1📚Graph Theory Notes
🧑💼 author: Vadim Lozin in Institute of Mathematics University of Warwick
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📲Channel: @ComplexNetworkAnalysis
#Booklet #graph
📄Spatial social network research: a bibliometric analysis
📘 journal: Computational Urban Science
🗓Publish year: 2022
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📱Channel: @ComplexNetworkAnalysis
#paper #Spatial #research #bibliometric
📄Spatial social network research: a bibliometric analysis
📘 journal: Computational Urban Science
🗓Publish year: 2022
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📱Channel: @ComplexNetworkAnalysis
#paper #Spatial #research #bibliometric
📄Information cascades in complex networks
📘 journal: Journal of Complex Networks (I.F=1.492)
🗓Publish year: 2017
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📲Channel: @ComplexNetworkAnalysis
#paper #graph #cascades #review
📄 Survey of Deep Graph Clustering: Taxonomy,Challenge, Application, and Open Resource
🗓Publish year: 2023
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📱Channel: @ComplexNetworkAnalysis
#paper #Deep #Graph #Clustering #Taxonomy #Challenge #Application #Open_Resource #survey
+1📄Machine Learning for Anomaly Detection: A Systematic Review
📘 journal: IEEE Acess (I.F=3.476)
🗓Publish year: 2021
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📲Channel: @ComplexNetworkAnalysis
#paper #graph #Anomaly_detection #review
📄A Survey on Graph Counterfactual Explanations: Definitions, Methods, Evaluation, and Research Challenges
📘 journal: ACM Computing Surveys (I.F=16.6)
🗓Publish year: 2023
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📱Channel: @ComplexNetworkAnalysis
#paper #Graph #Counterfactual #Explanations #Evaluation #Challenges #survey
📄 A Survey on Graph Neural Networks for Time Series: Forecasting, Classification, Imputation, and Anomaly Detection
🗓Publish year: 2023
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📲Channel: @ComplexNetworkAnalysis
#paper #survey #GNN #anomaly_detection #time_series
📄Privacy-Preserving Graph Machine Learning from Data to Computation: A Survey
🗓Publish year: 2023
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📱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 Mining (SNAM) (I.F=2.8)
🗓Publish year: 2023
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📱Channel: @ComplexNetworkAnalysis
#paper #Influence #maximization #behaviour_aware #survey
📄 A comprehensive survey of personal knowledge graphs
📘 journal: wiley(I.F=13.3)
🗓Publish year: 2023
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📲Channel: @ComplexNetworkAnalysis
#paper #survey #knowledge_graphs
+1📄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
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📲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 year: 2023
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📱Channel: @ComplexNetworkAnalysis
#paper #Community_Detection #Healthcare #Applications #review
📄Graph Convolutional Networks: Introduction to GNNs
💥Technical paper
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📲Channel: @ComplexNetworkAnalysis
#paper #Graph #GNN
📄Graph Theory
🧑🏻💼 author : Marc Lackenby
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📲Channel: @ComplexNetworkAnalysis
#paper #graph
📄Graph Data Structure And Algorithms
💥Technical paper
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📲Channel: @ComplexNetworkAnalysis
#paper #Graph #Data_Structure #Algorithms
