The paper surveys neural-symbolic reasoning over knowledge graphs from a query perspective. It reviews various query types and classifies neural symbolic reasoning methods. The authors also explore the integration of knowledge graph reasoning with large language models, highlighting their potential for groundbreaking advancements in fields like data mining, AI, and social sciences. --- Why it matters: This matters to researchers because it provides a comprehensive overview of current methods and future directions in knowledge graph reasoning, which is crucial for developing more interpretable and explainable AI systems. Source: https://arxiv.org/abs/2412.10390