Knowledge Graph Reasoning: A Neuro-Symbolic Perspective

Author:   Kewei Cheng ,  Yizhou Sun
Publisher:   Springer International Publishing AG
ISBN:  

9783031720109


Pages:   196
Publication Date:   22 November 2025
Format:   Paperback
Availability:   Manufactured on demand   Availability explained
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Knowledge Graph Reasoning: A Neuro-Symbolic Perspective


Overview

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.  To this end, logic and deep neural network models are studied together as integrated models of computation.  This book is written for readers who are interested in KG reasoning and the new perspective of neuro-symbolic integration and have prior knowledge to neural networks and deep learning.  The authors first provide a preliminary introduction to logic and background knowledge closely related to the surveyed techniques such as the introduction of knowledge graph and ontological schema and the technical foundations of first-order logic learning.  Reasoning techniques for knowledge graph completion are presented from three perspectives, including: representation learning-based, logical, and neuro-symbolic integration.  The book then explores question answering on KGs with specific focus on multi-hop and complex-logic query answering before outlining work that addresses the rule learning problem.  The final chapters highlight foundations on ontological schema and introduce its usage in KG before closing with open research questions and a discussion on the potential directions in the future of the field.

Full Product Details

Author:   Kewei Cheng ,  Yizhou Sun
Publisher:   Springer International Publishing AG
Imprint:   Springer International Publishing AG
ISBN:  

9783031720109


ISBN 10:   3031720105
Pages:   196
Publication Date:   22 November 2025
Audience:   General/trade ,  General
Format:   Paperback
Publisher's Status:   Active
Availability:   Manufactured on demand   Availability explained
We will order this item for you from a manufactured on demand supplier.

Table of Contents

Introduction.- Preliminaries on Knowledge Graph and Symbolic Logic.- Knowledge Graph Completion.- Complex Query Answering.-Logical Rule Learning.- Incorporating Ontology to Knowledge Graph Reasoning.- Conclusion and Research Frontiers.

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Author Information

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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