Format:
1 Online-Ressource(XXI, 220 p.)
Edition:
1st ed. 2021.
ISBN:
9783031015908
Series Statement:
Synthesis Lectures on Artificial Intelligence and Machine Learning
Content:
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.
Content:
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.
Additional Edition:
ISBN 9783031000355
Additional Edition:
ISBN 9783031004629
Additional Edition:
ISBN 9783031027185
Additional Edition:
Erscheint auch als Druck-Ausgabe ISBN 9783031000355
Additional Edition:
Erscheint auch als Druck-Ausgabe ISBN 9783031004629
Additional Edition:
Erscheint auch als Druck-Ausgabe ISBN 9783031027185
Language:
English
DOI:
10.1007/978-3-031-01590-8
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