Knowledge Graph Reasoning

A Neuro-Symbolic Perspective

Inbunden, Engelska, 2024

AvKewei Cheng,Yizhou Sun

549 kr

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This book provides a coherent and unifying view for logic and representation learning to contribute to knowledge graph (KG) reasoning and produce better computational tools for integrating both worlds.

Produktinformation

Utgivningsdatum2024-11-22
Mått168 x 240 x 17 mm
Vikt532 g
FormatInbunden
SpråkEngelska
SerieSynthesis Lectures on Data, Semantics, and Knowledge
Antal sidor196
FörlagSpringer International Publishing AG
ISBN9783031720079

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Kewei Cheng, Ph.D., is an applied scientist at Amazon. She earned her Ph.D. in Computer Science from UCLA in 2024. Her main research areas include graph and network mining as well as broader interests in data mining and machine learning. Dr. Cheng’s work has been featured in various prestigious conferences across multiple domains such as KDD, VLDB, WSDM, CIKM, AAAI, ICLR, EMNLP, and ACL.Yizhou Sun, Ph.D., is a Professor in the Department of Computer Science at UCLA. Her principal research interest is on mining graphs/networks and more generally in data mining and machine learning with a recent focus on deep learning on graphs and neuro-symbolic reasoning. Dr. Sun is a recipient of multiple Best Paper Awards, two Test of Time Awards, among many other awards. She has also served as organizers of top conferences in the field, such as KDD’23, ICLR’24, and KDD’25.

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Knowledge Graphs

Aidan Hogan, Eva Blomqvist, Michael Cochez, Claudia d’Amato, Gerard de Melo, Claudio Gutierrez, Sabrina Kirrane, Jose Emilio Labra Gayo, Roberto Navigli, Sebastian Neumaier, Axel Polleres, Sabbir Rashid, Anisa Rula, Antoine Zimmermann, Lukas Schmelzeisen, Axel-Cyrille Ngonga Ngomo, Juan Sequeda, Steffen Staab, Claudia D'Amato