Heterogeneous Graph Representation Learning and Applications

31.01.2022

Englisch

9789811661655

Springer Singapore

Artificial Intelligence: Foundations, Theory, and Algorithms

Nein

Chuan Shi, Xiao Wang, Philip S. Yu

318

Gebundene Ausgabe

Chuan Shi is the professor in School of Computer Sciences of Beijing University of Posts and Telecommunications, deputy director of Beijing Key Lab of Intelligent Telecommunication Software and Multimedia. The main research interests include data mining, machine learning, artificial intelligence 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, AAAI, IJCAI, and WWW. And in the meanwhile, his first monograph about heterogeneous information networks has been published by Springer. He has been honored as the best paper award in ADMA 2011 and ADMA 2018, and has guided students to the world champion in the IJCAI Contest 2015, the premier international data mining competition. He is also the recipient of “the Youth Talent Plan” and “the Pioneer of Teacher's Ethics” in Beijing.

Heterogeneous graph, heterogeneous information network, social network analysis, network embedding, network represenation, data mining, machine learning, graph neural network, deep neural network, attention mechnism

UNF - Data Mining UYQE - Wissensbasierte Systeme, Expertensysteme UYQM - Maschinelles Lernen UN - Datenbanken

235 mm

15.5 cm