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Building a reverse dictionary with specific application to the COVID-19 pandemic
Bushra Siddique1, M M Sufyan Beg1
1Department of Computer Engineering, Aligarh Muslim University, Aligarh, India.
International Journal of Information Technology : an Official Journal of Bharati Vidyapeeth'S Institute of Computer Applications and Management
|June 15, 2022
Summary
A new reverse dictionary was developed to help users find COVID-19 specific terms. This tool assists diverse language producers in accurately describing concepts related to the pandemic.
Area of Science:
- Computational Linguistics
- Natural Language Processing
- Lexicography
Background:
- The COVID-19 pandemic generated a vast amount of specialized text across various domains.
- Effective communication regarding COVID-19 is hindered by its unique and unfamiliar glossary for many language producers.
- Existing tools may not adequately address the specific vocabulary needs arising from the pandemic.
Purpose of the Study:
- To develop and evaluate a Reverse Dictionary tailored for the COVID-19 pandemic's specific terminology.
- To assist a wide range of users, from medical professionals to the general public, in finding appropriate words for pandemic-related concepts.
- To enhance the accuracy and accessibility of language used in COVID-19 related communication.
Main Methods:
- Implementation of a Reverse Dictionary system based on the Wordster architecture.
- Benchmarking against the commercial Onelook Reverse Dictionary.
- Incorporation of Zadeh's paradigm from the Computational Theory of Perceptions to address limitations.
Main Results:
- The developed system achieved an accuracy of 0.49 based on top-3 system responses.
- The Wordster-based architecture outperformed the Onelook Reverse Dictionary benchmark.
- A comprehensive COVID-19 glossary was compiled as a valuable resource.
Conclusions:
- The study demonstrates the feasibility and utility of a specialized Reverse Dictionary for pandemic-specific language.
- The implemented system offers a valuable tool for improving clarity and precision in COVID-19 communication.
- Future work may involve refining the system using principles from the Computational Theory of Perceptions for enhanced performance.
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