Titlebook: Knowledge Graph Reasoning; A Neuro-Symbolic Per Kewei Cheng,Yizhou Sun Book 2025 The Editor(s) (if applicable) and The Author(s), under exc

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2691-2023 roaches.Provides a principled theoretical view and gives dee.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 n

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Logical Rule Learning,n, the state-of-the-art approach called RLogic [.] has been introduced. RLogic does not solely rely on rule instances but suggests learning logical rules directly at the schema level and pushing deductive reasoning deep into the learning process.

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Incorporating Ontology to Knowledge Graph Reasoning,ant to note that both cross-view connections and intra-view structures in KG ontologies are essential for KG reasoning. We introduce JOIE [.] as the most representative work that effectively utilizes both pieces of information in a joint manner.

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Kewei Cheng,Yizhou SunFocuses on neural-symbolic integration on KG reasoning to unify the modern representation approaches with traditional symbolic reasoning approaches.Provides a principled theoretical view and gives dee

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Knowledge Graph Reasoning978-3-031-72008-6Series ISSN 2691-2023 Series E-ISSN 2691-2031