Heterogeneous Graph Representation Learning and Applications (Artificial Intelligence: Foundations, Theory, and Algorithms)
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Heterogeneous Graph Representation Learning and Applications (Artificial Intelligence: Foundations, Theory, and Algorithms)

by Chuan Shi, Xiao Wang, Philip S. Yu

artificial intelligence Machine Learning Graph Theory
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Explores heterogeneous graph representation learning, its theoretical foundations, and practical applications in artificial intelligence and data analysis.

ISBN-13 9789811661655 ASIN 9811661650 Views 97 Publisher Springer Year 2022 Edition 2022 ed. Format Hardcover Product Group Book Pages 338 Created April 04, 2026 Updated September 29, 2026
About This Book

This book explores heterogeneous graph representation learning within the field of artificial intelligence.

It covers foundational theory and algorithmic approaches for processing complex graph data.

The text is part of the Artificial Intelligence: Foundations, Theory, and Algorithms series.

Authored by Chuan Shi, Xiao Wang, and Philip S. Yu.

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I will be using this book for: