Knowledge Graph Reasoning, A Neuro-Symbolic Perspective

Knowledge Graph Reasoning: A Neuro-Symbolic Perspective

Architect your relational logic and master the high-performance protocols of modern neuro-symbolic engineering. Knowledge Graph Reasoning: A Neuro-Symbolic Perspective provides a definitive, intelligence-first roadmap to the most significant shift in AI-driven discovery since the digital revolution. Learn how to move beyond simple triple-pattern matching to high-velocity, logic-integrated discovery—bridging the gap between a standalone neural network and a sophisticated, symbolic-integrated ecosystem—ensuring your technical projects are resilient, scalable, and ready for the 2026 global technology landscape.

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What You Will Learn:

Foundations of Neuro-Symbolic Architecture: Master the core principles of integrating symbolic logic with deep neural network models to create more interpretable AI systems.

Modern Reasoning Workflows: Step-by-step guidance on utilizing representation learning and logical rule mining to maintain peak operational integrity in your data queries.

Scalable Integration Patterns: Discover how to navigate multi-hop and complex-logic query answering to maintain the structural integrity and technical agility of your knowledge bases.

Strategic Security & Empirical Integrity: Learn advanced techniques for maintaining information security within your graph reasoning, protecting against incomplete data and ensuring the technical agility of your evidence-based AI delivery.

Who This Book is For: This professional-grade guide is essential for AI Researchers, Data Scientists, and Knowledge Engineers. It is an invaluable resource for any technical lead—including those building highly advanced, data-linked graduation projects like Smart Guard—aiming to master the structural integrity and technical agility required for modern, evidence-based software and system delivery.

Product Details:

Format: Digital PDF / EPUB Download

Authors: Kewei Cheng; Yizhou Sun

Publisher: Springer Nature Switzerland (Synthesis Lectures on Data, Semantics, and Knowledge)

ISBN-13: 9783031720079

ISBN-10: 3031720075