Knowledge Graph Reasoning : A Neuro-Symbolic Perspective / by Kewei Cheng, Yizhou Sun.

Format:

Book

Author/Creator:

Cheng, Kewei.

Contributor:

Sun, Yizhou.

Series:

Synthesis Lectures on Data, Semantics, and Knowledge, 2691-2031

Language:

English

Subjects (All):

Information retrieval.

Computer architecture.

Data structures (Computer science).

Information theory.

Coding theory.

Artificial intelligence.

Ontology.

Data Storage Representation.

Data Structures and Information Theory.

Coding and Information Theory.

Artificial Intelligence.

Local Subjects:

Data Storage Representation.

Data Structures and Information Theory.

Coding and Information Theory.

Artificial Intelligence.

Ontology.

Physical Description:

1 online resource (201 pages)

Edition:

1st ed. 2025.

Place of Publication:

Cham : Springer Nature Switzerland : Imprint: Springer, 2025.

Summary:

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.

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.

Notes:

Description based on publisher supplied metadata and other sources.

ISBN:

9783031720086

3031720083

OCLC:

1473149468