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Named Entity Recognition on CORD-19 Bio-Medical Dataset with Tolerance Rough Sets

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Transactions on Rough Sets XXIII

Part of the book series: Lecture Notes in Computer Science ((TRS,volume 13610))

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Abstract

Biomedical named entity recognition is becoming increasingly important to biomedical research due to a proliferation of articles and also due to the current pandemic disease. This paper addresses the task of automatically finding and recognizing biomedical entity types related to COVID (e.g., virus, cell, therapeutic) with tolerance rough sets. The task includes i) extracting nouns and their co-occurring contextual patterns from a large BioNER dataset related to COVID-19 and, ii) annotating unlabelled data with a semi-supervised learning algorithm using co-occurence statistics. 465,250 noun phrases and 6,222,196 contextual patterns were extracted from 29,500 articles using natural language text processing methods. Three categories were successfully classified at this time: virus, cell and therapeutic. Early precision@N results demonstrate that our proposed tolerant pattern learner (TPL) is able to constrain concept drift in all 3 categories during the iterative learning process.

S. Ramanna—This work is dedicated to Prof. Z. Pawlak on his \(95^{th}\) birthday.

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Notes

  1. 1.

    https://www.nlm.nih.gov/bsd/pmresources.html.

  2. 2.

    http://lemurproject.org/clueweb09/.

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Acknowledgments

Seeratpal’ s work was supported by University of Winnipeg 2020 and 2021 NSERC Undergraduate Research Award (USRA). Sheela Ramanna’ s was supported by NSERC Discovery Grant # 194376. The authors wish to acknowledge the help of Rajesh Jaiswal for preprocessing the dataset and Christopher Henry for providing the GPU computing platform.

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Authors and Affiliations

  1. Department of Computing Science, University of Alberta, Edmonton, AB, Canada

    Seeratpal Jaura

  2. University of Winnipeg, Winnipeg, MB, R3B 2E9, Canada

    Sheela Ramanna

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  1. Seeratpal Jaura
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  2. Sheela Ramanna
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Correspondence to Sheela Ramanna .

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Editors and Affiliations

  1. University of Manitoba, Winnipeg, MB, Canada

    James F. Peters

  2. Systems Research Institute, Polish Academy of Sciences, Warsaw, Poland

    Andrzej Skowron

  3. Tripura University, Agartala, India

    Rabi Nanda Bhaumik

  4. University of Winnipeg, Winnipeg, MB, Canada

    Sheela Ramanna

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Jaura, S., Ramanna, S. (2022). Named Entity Recognition on CORD-19 Bio-Medical Dataset with Tolerance Rough Sets. In: Peters, J.F., Skowron, A., Bhaumik, R.N., Ramanna, S. (eds) Transactions on Rough Sets XXIII. Lecture Notes in Computer Science(), vol 13610. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-66544-2_3

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  • DOI: https://doi.org/10.1007/978-3-662-66544-2_3

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