Research Topics in Knowledge Graph

Preliminaries: What is a Knowledge Graph?

A knowledge graph, also known as a semantic network, represents a network of real-world entities—i.e. objects, events, situations, or concepts—and illustrates the relationship between them. This information is usually stored in a graph database and visualized as a graph structure, prompting the term knowledge “graph.” [Source (IBM)]

We classify the common knowledge graph concepts you may come across as follows.

• Traditional knowledge graph curated or crowsourced by human.
  • There are general KGs such as Wikidata, DBPedia, Yago, Google Freebase.
  • There are also domain-specific KGs such as PrimeKG (Medical KG), and FinKario (Financial KG).
• Heterogenous information network (HIN) built on relational data, such as social network, financial network and product perchase network. It is also capable to store these data in relational table while relations are usually represented by the foreign keys between tables.
• Other self-defined heterogenous graphs or knowledge graph for specific tasks. For example,
  • The graph in Microsoft GraphRAG, while the nodes are entities extracted from documents and edges represent the co-occurence of these entities in the document chunks.
  • Agent Memory Graph in Graphiti or ByteDance M3-Agent.

Papers and Materials from All Areas

• Note 1: The papers from the database/data science communities are marked with 🌟.
• Note 2: From Nov 2023, I started to add papers related to LLM in each session, marked with 🔥.

0. Overview

• Survey of Knowledge Graphs - General Concepts, Scientific Problems, Applications, Challenges, and Directions) [link]

1. Knowledge Extraction and Integration to Construct KGs

• Knowledge Graph Construction (Demo or System) [link]

• About Domain-Specific Knowledge Bases [link]

• About Multi-Modal Knowledge Graph (MMKG) [link]

• Named Entity Recognition, Entity Extraction and Entity Typing [link]

• Coreference Resolution [link]

• Entity Linking and Entity Disambiguation [link]

• Entity Resolution, Entity Matching and Entity Alignment [link]

• General Relation Extraction [link]

• General Information Extraction and Open Information Extraction [link]

• Relation Linking and Relation Disambiguation [link]

2. Mining and Refinement of KGs

• Knowledge Graph Embedding, Learning, Reasoning, Rule Mining, and Path Finding [link]

• Knowledge Base Refinement (Incompleteness, Incorrectness, and Freshness) [link]

• Knowledge Fusion, Cleaning, Evaluation and Truth Discovery [link]

3. Applications Supported by KGs

• Knowledge Graph Question Answering (KGQA) [link]

• Knowledge Graph Recommendation [link]

• Knowledge Graph Enhanced Machine Learning [link]

• Knowledge Graphs and Large Language Models (LLMs) [link] 🔥🔥🔥

4. Schema and Query of KGs

• Knowledge Graph Representation (RDF and Property Graph), Schema and Query [link]

• Knowledge Graph Taxonomy/Ontology Construction and Improvement [link]

5. Others

• Graph Databases [Link]

• Other Interesting Research Works [link]

• Good DB Papers [link]

• Tutorials and Notes of Other Related Insightful Topics [Link]

Papers and Materials from the Database/Data Science Communities

Note: Papers from SIGMOD/VLDB/ICDE/KDD/TKDE/VLDBJ

[2018] [2019] [2020] [2021] [2022] [2023] [2024] [2025]

Tutorials and Notes from Talented People

Note: We only list the general tutorials here. For the surveys or communities of specific topics such as KG Construction, KG4LLM or KG Embedding, please refer to the above detailed sections.

Tutorials, Discussion, Courses and Communities

1. An introduction to knowledge graph and knowledge extraction from unstructured text. [Link]
2. Information Extraction by Niranjan Balasubramanian {Slides in my Mac}
3. CS 520 - Knowledge Graphs (seminar) - provided by Stanford
4. OpenKG.cn

GitHub Repos that Summarize the Papers/Projects/Data related to Knowledge Graphs

1. A Collection of KG Surveys, Papers (WWW+ACL+AAAI) and Data [GitHub]
2. KG SOTA [GitHub]
3. Awesome KG tutorials/papers/projects/communities [GitHub]
4. KG SOTA (Chinese) [Zhihu]
5. Tracking Progress in Natural Language Processing [GitHub]
6. KG Embedding SOTA [GitHub]
7. Entity Related Papers [GitHub]
8. Information Extraction Resources [GitHub]
9. KGQA [Giters]
10. Open-Environment Knowledge Graph Construction and Reasoning: Challenges, Approaches, and Opportunities [GitHub]
11. KG-LLM-Papers [Link]
12. Awesome LLM-KGs [Link]

Knowledge Graph Datasets

Note: We only list the general KGs here. For the datasets or benchmarks for specific topics such as KGQA or KG Completion, please refer to the above detailed sections.

1. WikiData
2. Yago
3. Google Knowledge Graph
4. Chinese OwnThink Knowledge Graph [Link]

Useful Tools or APIs

1. From Freebase to Wikidata: The Great Migration [Paper and useful links]
2. SPARQL tutorial [Link]
3. Installing and running ElasticSearch [Link]
4. Open KG on COVID-19 [Link]
5. BOOKNLP [Link] (Pronominal Coreference Resolution, a natural language processing pipeline that scales to books and other long documents (in English))
6. Wikidata Integrator [GitHub]
7. OpenTapioca [Link]
8. Grakn KGLIB (Knowledge Graph Library) [GitHub]
9. SPARQL server on Freebase [GitHub] [About VOS]
10. LATEX Code Search [Link]

I have listed more tools/benchmarks/APIs/demos in each sub-page of different topics in this repo. Feel free to check!