Yang, Cheng.
Network Embedding Theories, Methods, and Applications / [electronic resource] : by Cheng Yang, Zhiyuan Liu, Cunchao Tu, Chuan Shi, Maosong Sun. - 1st ed. 2021. - XXI, 220 p. online resource. - Synthesis Lectures on Artificial Intelligence and Machine Learning, 1939-4616 . - Synthesis Lectures on Artificial Intelligence and Machine Learning, .
Preface -- Acknowledgments -- The Basics of Network Embedding -- Network Embedding for General Graphs -- Network Embedding for Graphs with Node Attributes -- Revisiting Attributed Network Embedding: A GCN-Based Perspective -- Network Embedding for Graphs with Node Contents -- Network Embedding for Graphs with Node Labels -- Network Embedding for Community-Structured Graphs -- Network Embedding for Large-Scale Graphs -- Network Embedding for Heterogeneous Graphs -- Network Embedding for Social Relation Extraction -- Network Embedding for Recommendation Systems on LBSNs -- Network Embedding for Information Diffusion Prediction -- Future Directions of Network Embedding -- Bibliography -- Authors' Biographies.
heterogeneous graphs. Further, the book introduces different applications of NE such as recommendation and information diffusion prediction. Finally, the book concludes the methods and applications and looks forward to the future directions.
9783031015908
10.1007/978-3-031-01590-8 doi
Artificial intelligence.
Machine learning.
Neural networks (Computer science) .
Artificial Intelligence.
Machine Learning.
Mathematical Models of Cognitive Processes and Neural Networks.
Q334-342 TA347.A78
006.3
Network Embedding Theories, Methods, and Applications / [electronic resource] : by Cheng Yang, Zhiyuan Liu, Cunchao Tu, Chuan Shi, Maosong Sun. - 1st ed. 2021. - XXI, 220 p. online resource. - Synthesis Lectures on Artificial Intelligence and Machine Learning, 1939-4616 . - Synthesis Lectures on Artificial Intelligence and Machine Learning, .
Preface -- Acknowledgments -- The Basics of Network Embedding -- Network Embedding for General Graphs -- Network Embedding for Graphs with Node Attributes -- Revisiting Attributed Network Embedding: A GCN-Based Perspective -- Network Embedding for Graphs with Node Contents -- Network Embedding for Graphs with Node Labels -- Network Embedding for Community-Structured Graphs -- Network Embedding for Large-Scale Graphs -- Network Embedding for Heterogeneous Graphs -- Network Embedding for Social Relation Extraction -- Network Embedding for Recommendation Systems on LBSNs -- Network Embedding for Information Diffusion Prediction -- Future Directions of Network Embedding -- Bibliography -- Authors' Biographies.
heterogeneous graphs. Further, the book introduces different applications of NE such as recommendation and information diffusion prediction. Finally, the book concludes the methods and applications and looks forward to the future directions.
9783031015908
10.1007/978-3-031-01590-8 doi
Artificial intelligence.
Machine learning.
Neural networks (Computer science) .
Artificial Intelligence.
Machine Learning.
Mathematical Models of Cognitive Processes and Neural Networks.
Q334-342 TA347.A78
006.3