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Network Embedding Theories, Methods, and Applications

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

Bibliographic Details
Main Authors: Yang, Cheng, Liu, Zhiyuan (Author), Tu, Cunchao (Author), Shi, Chuan (Author)
Format: eBook
Language:English
Published: Cham Springer International Publishing 2021, 2021
Edition:1st ed. 2021
Series:Synthesis Lectures on Artificial Intelligence and Machine Learning
Subjects:
Machine Learning
Neural Networks (computer Science) 
Mathematical Models Of Cognitive Processes And Neural Networks
Artificial Intelligence
Online Access:
Collection: Springer eBooks 2005- - Collection details see MPG.ReNa
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245 0 0 |a Network Embedding  |h Elektronische Ressource  |b Theories, Methods, and Applications  |c by Cheng Yang, Zhiyuan Liu, Cunchao Tu, Chuan Shi, Maosong Sun 
250 |a 1st ed. 2021 
260 |a Cham  |b Springer International Publishing  |c 2021, 2021 
300 |a XXI, 220 p  |b online resource 
505 0 |a 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 
653 |a Machine Learning 
653 |a Neural networks (Computer science)  
653 |a Mathematical Models of Cognitive Processes and Neural Networks 
653 |a Machine learning 
653 |a Artificial Intelligence 
653 |a Artificial intelligence 
700 1 |a Liu, Zhiyuan  |e [author] 
700 1 |a Tu, Cunchao  |e [author] 
700 1 |a Shi, Chuan  |e [author] 
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490 0 |a Synthesis Lectures on Artificial Intelligence and Machine Learning 
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520 |a 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 

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