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All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year Sort by creator [A → Z]' creator [Z → A]' publishing year ↑ (asc)' publishing year ↓ (desc)' title [A → Z]' title [Z → A]' Simple Search Hits 1 – 9 of 9 1 Using natural language processing to extract health-related causality from Twitter messages ... Doan, Son; Yang, Elly W; Tilak, Sameer. - : arXiv, 2019 BASE Show details 2 Extracting health-related causality from twitter messages using natural language processing Doan, Son; Yang, Elly W.; Tilak, Sameer S.. - : BioMed Central, 2019 BASE Show details 3 A Preliminary Study of Clinical Concept Detection Using Syntactic Relations Torii, Manabu; Yang, Elly W.; Doan, Son. - : American Medical Informatics Association, 2018 BASE Show details 4 Rapid Adaptation of POS Tagging for Domain Specific Uses ... Miller, John E.; Bloodgood, Michael; Torii, Manabu. - : arXiv, 2014 BASE Show details 5 iSimp in BioC standard format: enhancing the interoperability of a sentence simplification system Peng, Yifan; Tudor, Catalina O.; Torii, Manabu. - : Oxford University Press, 2014 BASE Show details 6 BioC: a minimalist approach to interoperability for biomedical text processing Comeau, Donald C.; Islamaj Doğan, Rezarta; Ciccarese, Paolo. - : Oxford University Press, 2013 BASE Show details 7 BioC: a minimalist approach to interoperability for biomedical text processing Comeau, Donald C.; Islamaj Doğan, Rezarta; Ciccarese, Paolo. - : Oxford University Press, 2013 BASE Show details 8 Rapid Adaptation of POS Tagging for Domain Specific Uses ... Miller, John; Bloodgood, Michael; Torii, Manabu. - : Digital Repository at the University of Maryland, 2006 BASE Show details 9 Rapid Adaptation of POS Tagging for Domain Specific Uses Miller, John; Bloodgood, Michael; Torii, Manabu; Vijay-Shanker, K. - : Association for Computational Linguistics, 2006 Abstract: Part-of-speech (POS) tagging is a fundamental component for performing natural language tasks such as parsing, information extraction, and question answering. When POS taggers are trained in one domain and applied in significantly different domains, their performance can degrade dramatically. We present a methodology for rapid adaptation of POS taggers to new domains. Our technique is unsupervised in that a manually annotated corpus for the new domain is not necessary. We use suffix information gathered from large amounts of raw text as well as orthographic information to increase the lexical coverage. We present an experiment in the Biological domain where our POS tagger achieves results comparable to POS taggers specifically trained to this domain. Keyword: artificial intelligence; biomedical natural language processing; biomedical part-of-speech tagging; biomedical POS tagging; biomedical text processing; BioNLP; computational linguistics; computer science; domain adaptation; domain-specific part-of-speech tagging; domain-specific POS tagging; human language technology; machine learning; natural language processing; part-of-speech tagging; POS tagging; rapid adaptation; rapid domain adaptation; statistical methods; suffix-based part-of-speech tagging; suffix-based POS tagging; text processing; Transformation Based Learning; unsupervised domain adaptation URL: https://doi.org/10.13016/M2059S http://hdl.handle.net/1903/15583 BASE Hide details

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