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Using the pubannotation ecosystem to perform agile text mining on genomics & informatics: A tutorial review

Title
Using the pubannotation ecosystem to perform agile text mining on genomics & informatics: A tutorial review
Authors
Nam H.-J.Yamada R.Park H.-S.
Ewha Authors
박현석
SCOPUS Author ID
박현석scopus
Issue Date
2020
Journal Title
Genomics and Informatics
ISSN
2234-0742JCR Link
Citation
Genomics and Informatics vol. 18, no. 2, pp. 1 - 10
Keywords
Named entity recognitionNatural language processingText mining
Publisher
Korea Genome Organization
Indexed
SCOPUS scopus
Document Type
Review
Abstract
The prototype version of the full-text corpus of Genomics & Informatics has recently been archived in a GitHub repository. The full-text publications of volumes 10 through 17 are also directly downloadable from PubMed Central (PMC) as XML files. During the Biomedi-cal Linked Annotation Hackathon 6 (BLAH6), we experimented with converting, annotat-ing, and updating 301 PMC full-text articles of Genomics & Informatics using PubAnnota-tion, a system that provides a convenient way to add PMC publications based on PMCID. Thus, this review aims to provide a tutorial overview of practicing the iterative task of named entity recognition with the PubAnnotation/PubDictionaries/TextAE ecosystem. We also describe developing a conversion tool between the Genia tagger output and the JSON format of PubAnnotation during the hackathon. © 2020, Korea Genome Organization.
DOI
10.5808/GI.2020.18.2.e13
Appears in Collections:
인공지능대학 > 컴퓨터공학과 > Journal papers
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