TopEx: topic exploration of COVID-19 corpora - Results from the BioCreative VII Challenge Track 4.

Autor:	Olex AL; C. Kenneth and Diane Wright Center for Clinical and Translational Research, Virginia Commonwealth University, 203 E. Cary St, Richmond, VA 23291, USA.; Department of Computer Science, Virginia Commonwealth University, 401 S. Main St, Richmond, VA 23284, USA., French E; C. Kenneth and Diane Wright Center for Clinical and Translational Research, Virginia Commonwealth University, 203 E. Cary St, Richmond, VA 23291, USA.; Department of Computer Science, Virginia Commonwealth University, 401 S. Main St, Richmond, VA 23284, USA., Burdette P; C. Kenneth and Diane Wright Center for Clinical and Translational Research, Virginia Commonwealth University, 203 E. Cary St, Richmond, VA 23291, USA., Sagiraju S; C. Kenneth and Diane Wright Center for Clinical and Translational Research, Virginia Commonwealth University, 203 E. Cary St, Richmond, VA 23291, USA., Neumann T; Massey Cancer Center, Virginia Commonwealth University, 401 S. Main St, Richmond, VA 23284, USA., Gal TS; C. Kenneth and Diane Wright Center for Clinical and Translational Research, Virginia Commonwealth University, 203 E. Cary St, Richmond, VA 23291, USA.; Massey Cancer Center, Virginia Commonwealth University, 401 S. Main St, Richmond, VA 23284, USA., McInnes BT; Department of Computer Science, Virginia Commonwealth University, 401 S. Main St, Richmond, VA 23284, USA.
Jazyk:	angličtina
Zdroj:	Database : the journal of biological databases and curation [Database (Oxford)] 2022 Aug 11; Vol. 2022.
DOI:	10.1093/database/baac063
Abstrakt:	TopEx is a natural language processing application developed to facilitate the exploration of topics and key words in a set of texts through a user interface that requires no programming or natural language processing knowledge, thus enhancing the ability of nontechnical researchers to explore and analyze textual data. The underlying algorithm groups semantically similar sentences together followed by a topic analysis on each group to identify the key topics discussed in a collection of texts. Implementation is achieved via a Python library back end and a web application front end built with React and D3.js for visualizations. TopEx has been successfully used to identify themes, topics and key words in a variety of corpora, including Coronavirus disease 2019 (COVID-19) discharge summaries and tweets. Feedback from the BioCreative VII Challenge Track 4 concludes that TopEx is a useful tool for text exploration for a variety of users and tasks. Databse Url: http://topex.cctr.vcu.edu. (© The Author(s) 2022. Published by Oxford University Press.)
Databáze:	MEDLINE
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