# Covidia: COVID-19 Interdisciplinary Academic Knowledge Graph

arXiv: https://arxiv.org/abs/2304.07242 · HTML: https://mlsanity.com/paper/2304.07242/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 15 of its 42 references that are in the map.
- First posted on arXiv 14 Apr 2023.

## Builds on (most cited first, 15 of 15)

- [BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding](https://mlsanity.com/paper/1810.04805/) (2018)
- [Representation Learning with Contrastive Predictive Coding](https://mlsanity.com/paper/1807.03748/) (2018)
- [Bidirectional LSTM-CRF Models for Sequence Tagging](https://mlsanity.com/paper/1508.01991/) (2015)
- [How to Fine-Tune BERT for Text Classification?](https://mlsanity.com/paper/1905.05583/) (2019)
- [CORD-19: The COVID-19 Open Research Dataset](https://mlsanity.com/paper/2004.10706/) (2020)
- [Hierarchical Transformers for Long Document Classification](https://mlsanity.com/paper/1910.10781/) (2019)
- [Supporting Clustering with Contrastive Learning](https://mlsanity.com/paper/2103.12953/) (2021)
- [Automated Phrase Mining from Massive Text Corpora](https://mlsanity.com/paper/1702.04457/) (2017)
- [OpenNRE: An Open and Extensible Toolkit for Neural Relation Extraction](https://mlsanity.com/paper/1909.13078/) (2019)
- [COVID-19 Literature Knowledge Graph Construction and Drug Repurposing Report Generation](https://mlsanity.com/paper/2007.00576/) (2020)
- [COVID-19 Knowledge Graph: Accelerating Information Retrieval and Discovery for Scientific Literature](https://mlsanity.com/paper/2007.12731/) (2020)
- [Document Classification for COVID-19 Literature](https://mlsanity.com/paper/2006.13816/) (2020)
- [Artificial Intelligence (AI) in Action: Addressing the COVID-19 Pandemic with Natural Language Processing (NLP)](https://mlsanity.com/paper/2010.16413/) (2020)
- [Label-aware Document Representation via Hybrid Attention for Extreme Multi-Label Text Classification](https://mlsanity.com/paper/1905.10070/) (2019)
- [COVIDScholar: An automated COVID-19 research aggregation and analysis platform](https://mlsanity.com/paper/2012.03891/) (2020)

## Abstract (arXiv)

The pandemic of COVID-19 has inspired extensive works across different research fields. Existing literature and knowledge platforms on COVID-19 only focus on collecting papers on biology and medicine, neglecting the interdisciplinary efforts, which hurdles knowledge sharing and research collaborations between fields to address the problem. Studying interdisciplinary researches requires effective paper category classification and efficient cross-domain knowledge extraction and integration. In this work, we propose Covidia, COVID-19 interdisciplinary academic knowledge graph to bridge the gap between knowledge of COVID-19 on different domains. We design frameworks based on contrastive learning for disciplinary classification, and propose a new academic knowledge graph scheme for entity extraction, relation classification and ontology management in accordance with interdisciplinary researches. Based on Covidia, we also establish knowledge discovery benchmarks for finding COVID-19 research communities and predicting potential links.