Network Embedding
Theories, Methods, and Applications
Published on 23. March 2021
Book
Paperback/Softback
XXI, 220 pages
978-3-031-00462-9 (ISBN)
Description
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.
More details
Series
Language
English
Place of publication
Cham
Switzerland
Publishing group
Springer International Publishing
Target group
Professional and scholarly
Illustrations
XXI, 220 p.
Dimensions
Height: 235 mm
Width: 191 mm
Thickness: 14 mm
Weight
464 gr
ISBN-13
978-3-031-00462-9 (9783031004629)
DOI
10.1007/978-3-031-01590-8
Schweitzer Classification
Other editions
Additional editions
E-Book
05/2022
Springer
€64.19
Available for download
Persons
Cheng Yang is an assistant professor in the School of Computer Science, Beijing University of Posts and Telecommunications, China. He received his B.E. and Ph.D. degrees in Computer Science from Tsinghua University in 2014 and 2019, respectively. His research interests include network representation learning, social computing, and natural language processing. He has published more than 20 papers in top-tier conferences and journals including AAAI, ACL, ACM TOIS, and IEEE TKDE.Zhiyuan Liu is an associate professor in the Department of Computer Science and Technology, Tsinghua University, China. He got his B.E. in 2006 and his Ph.D. in 2011 from the Depart ment of Computer Science and Technology, Tsinghua University. His research interests are natural language processing and social computation. He has published over 60 papers in international journals and conferences, including IJCAI, AAAI, ACL, and EMNLP, and received more than 10,000 citations according to Google Scholar.Cunchao Tu is a postdoc in the Department of Computer Science and Technology, Tsinghua University. He got his B.E. and Ph.D. in 2013 and 2018 from the Department of Computer Science and Technology, Tsinghua University. His research interests include network represen tation learning, social computing, and legal intelligence. He has published over 20 papers in international journals and conferences including IEEE TKDE, AAAI, ACL, and EMNLP.Chuan Shi is a professor in the School of Computer Sciences of Beijing University of Posts and Telecommunications. His main research interests include data mining, machine learning, and big data analysis. He has published more than 100 refereed papers, including top journals and conferences in data mining, such as IEEE TKDE, ACM TIST, KDD, WWW, AAAI, and IJCAI.Maosong Sun is a professor of the Department of Computer Science and Technology, and the Executive Vice President of Institute of Artificial Intelligence at Tsinghua University. His research interests include natural language processing, internet intelligence, machine learning, social computing, and computational education. He was elected as a foreign member of the Academia Europaea in 2020. He has published more than 200 papers in top-tier conferences and journals and received more than 15,000 citations according to Google Scholar.
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.