This repository serves as a curated collection of research papers, tutorials, and resources focused on Knowledge Graphs (KGs). It aims to provide a comprehensive overview and practical guidance for researchers and practitioners interested in KG construction, mining, applications, and related technologies, with recent additions covering Large Language Models (LLMs) and KGs.

How It Works

The repository organizes KG-related materials into thematic categories, including knowledge extraction, KG mining and refinement, applications (like KGQA and KG recommendations), schema and querying, and broader topics like LLMs and graph-based machine learning. It links to papers, GitHub repositories, tutorials, and courses, facilitating a structured exploration of the field.

Quick Start & Requirements

• No installation or execution commands are provided as this is a curated list of resources.
• Requirements are dependent on the specific papers or tools linked within the repository.
• Links to relevant resources are provided throughout the README.

Highlighted Details

• Comprehensive categorization of KG research topics.
• Inclusion of papers from major database and data science communities (SIGMOD, VLDB, KDD, etc.).
• Recent focus on the intersection of Knowledge Graphs and Large Language Models (LLMs), marked with 🔥.
• Links to numerous GitHub repositories that aggregate KG papers, surveys, and state-of-the-art implementations.

Maintenance & Community

• The repository is actively maintained, with new sections on LLMs added in November 2023.
• Links to various GitHub repositories and community discussions (e.g., Zhihu) are provided, indicating community engagement.

Licensing & Compatibility

• Licensing information is not explicitly stated for the repository itself, but it links to various external resources, each with its own license.
• Compatibility for commercial use or closed-source linking would depend on the licenses of the individual linked papers and tools.

Limitations & Caveats

The repository is a curated list and does not provide executable code or a unified framework. Users must navigate to individual linked resources to access papers, code, or tutorials, and their usability or licensing will vary.