# Domain-specific Knowledge Graphs: A survey

arXiv: https://arxiv.org/abs/2011.00235 · HTML: https://mlsanity.com/paper/2011.00235/

## Key facts

- Cited by 68 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 31 Oct 2020.

## Built on by (most cited first, 30 of 68)

- [Unifying Large Language Models and Knowledge Graphs: A Roadmap](https://mlsanity.com/paper/2306.08302/) (2023)
- [Knowledge Graphs: Opportunities and Challenges](https://mlsanity.com/paper/2303.13948/) (2023)
- [KG-RAG: Bridging the Gap Between Knowledge and Creativity](https://mlsanity.com/paper/2405.12035/) (2024)
- [A Decade of Knowledge Graphs in Natural Language Processing: A Survey](https://mlsanity.com/paper/2210.00105/) (2022)
- [Evaluating LLM -- Generated Multimodal Diagnosis from Medical Images and Symptom Analysis](https://mlsanity.com/paper/2402.01730/) (2024)
- [AutoKG: Efficient Automated Knowledge Graph Generation for Language Models](https://mlsanity.com/paper/2311.14740/) (2023)
- [Abstractive Text Summarization: State of the Art, Challenges, and Improvements](https://mlsanity.com/paper/2409.02413/) (2024)
- [Domain-Specific Retrieval-Augmented Generation Using Vector Stores, Knowledge Graphs, and Tensor Factorization](https://mlsanity.com/paper/2410.02721/) (2024)
- [A Symmetric Dual Encoding Dense Retrieval Framework for Knowledge-Intensive Visual Question Answering](https://mlsanity.com/paper/2304.13649/) (2023)
- [CTINexus: Automatic Cyber Threat Intelligence Knowledge Graph Construction Using Large Language Models](https://mlsanity.com/paper/2410.21060/) (2024)
- [A Review on Knowledge Graphs for Healthcare: Resources, Applications, and Promises](https://mlsanity.com/paper/2306.04802/) (2023)
- [AssertionForge: Enhancing Formal Verification Assertion Generation with Structured Representation of Specifications and RTL](https://mlsanity.com/paper/2503.19174/) (2025)
- [Construction of Knowledge Graphs: State and Challenges](https://mlsanity.com/paper/2302.11509/) (2023)
- [Mindful-RAG: A Study of Points of Failure in Retrieval Augmented Generation](https://mlsanity.com/paper/2407.12216/) (2024)
- [Pre-Training Multi-Modal Dense Retrievers for Outside-Knowledge Visual Question Answering](https://mlsanity.com/paper/2306.16478/) (2023)
- [Knowledge Graphs in Practice: Characterizing their Users, Challenges, and Visualization Opportunities](https://mlsanity.com/paper/2304.01311/) (2023)
- [Ontology-Aware RAG for Improved Question-Answering in Cybersecurity Education](https://mlsanity.com/paper/2412.14191/) (2024)
- [Sample-Efficient Learning of Novel Visual Concepts](https://mlsanity.com/paper/2306.09482/) (2023)
- [OntoAligner: A Comprehensive Modular and Robust Python Toolkit for Ontology Alignment](https://mlsanity.com/paper/2503.21902/) (2025)
- [Patient-Centric Knowledge Graphs: A Survey of Current Methods, Challenges, and Applications](https://mlsanity.com/paper/2402.12608/) (2024)
- [LinkQ: An LLM-Assisted Visual Interface for Knowledge Graph Question-Answering](https://mlsanity.com/paper/2406.06621/) (2024)
- [Knowledge Graphs Querying](https://mlsanity.com/paper/2305.14485/) (2023)
- [Synthesizing Event-centric Knowledge Graphs of Daily Activities Using Virtual Space](https://mlsanity.com/paper/2307.16206/) (2023)
- [Leveraging Large Language Models for Semantic Query Processing in a Scholarly Knowledge Graph](https://mlsanity.com/paper/2405.15374/) (2024)
- [Refining Diagnosis Paths for Medical Diagnosis based on an Augmented Knowledge Graph](https://mlsanity.com/paper/2204.13329/) (2022)
- [KGxBoard: Explainable and Interactive Leaderboard for Evaluation of Knowledge Graph Completion Models](https://mlsanity.com/paper/2208.11024/) (2022)
- [Question Answering Over Biological Knowledge Graph via Amazon Alexa](https://mlsanity.com/paper/2210.06040/) (2022)
- [Automating construction contract review using knowledge graph-enhanced large language models](https://mlsanity.com/paper/2309.12132/) (2023)
- [A Comprehensive Survey of Document-level Relation Extraction (2016-2023)](https://mlsanity.com/paper/2309.16396/) (2023)
- [CleanGraph: Human-in-the-loop Knowledge Graph Refinement and Completion](https://mlsanity.com/paper/2405.03932/) (2024)

## Abstract (arXiv)

Knowledge Graphs (KGs) have made a qualitative leap and effected a real revolution in knowledge representation. This is leveraged by the underlying structure of the KG which underpins a better comprehension, reasoning and interpretation of knowledge for both human and machine. Therefore, KGs continue to be used as the main means of tackling a plethora of real-life problems in various domains. However, there is no consensus in regard to a plausible and inclusive definition of a domain-specific KG. Further, in conjunction with several limitations and deficiencies, various domain-specific KG construction approaches are far from perfect. This survey is the first to offer a comprehensive definition of a domain-specific KG. Also, the paper presents a thorough review of the state-of-the-art approaches drawn from academic works relevant to seven domains of knowledge. An examination of current approaches reveals a range of limitations and deficiencies. At the same time, uncharted territories on the research map are highlighted to tackle extant issues in the literature and point to directions for future research.