# COVID-19 Knowledge Graph: Accelerating Information Retrieval and Discovery for Scientific Literature

arXiv: https://arxiv.org/abs/2007.12731 · HTML: https://mlsanity.com/paper/2007.12731/

## Key facts

- Cited by 14 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 24 Jul 2020.

## Built on by (most cited first, 14 of 14)

- [Knowledge Graphs: Opportunities and Challenges](https://mlsanity.com/paper/2303.13948/) (2023)
- [Knowledge Graph Embedding: A Survey from the Perspective of Representation Spaces](https://mlsanity.com/paper/2211.03536/) (2022)
- [A Review of Biomedical Datasets Relating to Drug Discovery: A Knowledge Graph Perspective](https://mlsanity.com/paper/2102.10062/) (2021)
- [Schema-aware Reference as Prompt Improves Data-Efficient Knowledge Graph Construction](https://mlsanity.com/paper/2210.10709/) (2022)
- [Large-Scale Knowledge Synthesis and Complex Information Retrieval from Biomedical Documents](https://mlsanity.com/paper/2302.06854/) (2023)
- [Zero-shot Medical Entity Retrieval without Annotation: Learning From Rich Knowledge Graph Semantics](https://mlsanity.com/paper/2105.12682/) (2021)
- [CleanGraph: Human-in-the-loop Knowledge Graph Refinement and Completion](https://mlsanity.com/paper/2405.03932/) (2024)
- [Accelerating COVID-19 research with graph mining and transformer-based learning](https://mlsanity.com/paper/2102.07631/) (2021)
- [Neural Entity Recognition with Gazetteer based Fusion](https://mlsanity.com/paper/2105.13225/) (2021)
- [Recognizing and Extracting Cybersecurtity-relevant Entities from Text](https://mlsanity.com/paper/2208.01693/) (2022)
- [SKG: A Versatile Information Retrieval and Analysis Framework for Academic Papers with Semantic Knowledge Graphs](https://mlsanity.com/paper/2306.04758/) (2023)
- [Exploring the evolution of research topics during the COVID-19 pandemic](https://mlsanity.com/paper/2310.03928/) (2023)
- [Covidia: COVID-19 Interdisciplinary Academic Knowledge Graph](https://mlsanity.com/paper/2304.07242/) (2023)
- [An Information Retrieval and Extraction Tool for Covid-19 Related Papers](https://mlsanity.com/paper/2401.16430/) (2024)

## Abstract (arXiv)

The coronavirus disease (COVID-19) has claimed the lives of over 350,000 people and infected more than 6 million people worldwide. Several search engines have surfaced to provide researchers with additional tools to find and retrieve information from the rapidly growing corpora on COVID-19. These engines lack extraction and visualization tools necessary to retrieve and interpret complex relations inherent to scientific literature. Moreover, because these engines mainly rely upon semantic information, their ability to capture complex global relationships across documents is limited, which reduces the quality of similarity-based article recommendations for users. In this work, we present the COVID-19 Knowledge Graph (CKG), a heterogeneous graph for extracting and visualizing complex relationships between COVID-19 scientific articles. The CKG combines semantic information with document topological information for the application of similar document retrieval. The CKG is constructed using the latent schema of the data, and then enriched with biomedical entity information extracted from the unstructured text of articles using scalable AWS technologies to form relations in the graph. Finally, we propose a document similarity engine that leverages low-dimensional graph embeddings from the CKG with semantic embeddings for similar article retrieval. Analysis demonstrates the quality of relationships in the CKG and shows that it can be used to uncover meaningful information in COVID-19 scientific articles. The CKG helps power www.cord19.aws and is publicly available.