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A Web Resource for Exploring the CORD-19 Dataset Using Root- and Rule-Based Phrases.

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Summary
This summary is machine-generated.

This paper introduces the NIST CORD-19 Web Resource, a tool for exploring COVID-19 research. It uses a novel linguistic method to improve search and analysis of the COVID-19 Open Research Dataset (CORD-19).

Keywords:
Auto-suggest searchCORD-19 datasetRoot- and rule-based method

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Area of Science:

  • Information Science
  • Computational Linguistics
  • Biomedical Informatics

Background:

  • The COVID-19 Open Research Dataset (CORD-19) is a large, heterogeneous collection of documents.
  • Effective exploration and analysis of CORD-19 are crucial for understanding the pandemic.
  • Existing search methods may struggle with the complexity and scale of biomedical literature.

Purpose of the Study:

  • To describe a new web resource, the NIST CORD-19 Web Resource, for community exploration of CORD-19.
  • To introduce and demonstrate the utility of the NIST-developed Root- and Rule-based method for text analysis.
  • To showcase how linguistic structures can enhance search, topic modeling, and trend analysis within a large document corpus.

Main Methods:

  • Development of the NIST CORD-19 Web Resource.
  • Application of the NIST Root- and Rule-based method to exploit linguistic structures in text.
  • Implementation of auto-suggesting related terms for refined search.
  • Generation of taxonomic structures and semantic relationships between terms.
  • Utilization of a novel search engine to demonstrate capabilities.

Main Results:

  • The NIST CORD-19 Web Resource provides tools for community exploration of CORD-19.
  • The Root- and Rule-based method enables auto-suggestion of related terms, improving search refinement.
  • The method generates valuable taxonomic and semantic information about terms within the corpus.
  • The developed search engine effectively demonstrates the resource's capabilities for discovery and analysis.

Conclusions:

  • The NIST CORD-19 Web Resource offers a powerful platform for navigating and analyzing COVID-19 research.
  • The Root- and Rule-based linguistic method significantly enhances information retrieval and understanding of complex datasets.
  • This approach provides a foundation for advanced topic modeling and trend analysis tools in biomedical research.