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Domain Adaptation in Part-of-Speech Tagging

Domain Adaptation in Part-of-Speech Tagging

Miriam Lúcia Domingues, Eloi Luiz Favero
Copyright: © 2013 |Pages: 21
ISBN13: 9781466621695|ISBN10: 1466621699|EISBN13: 9781466621701
DOI: 10.4018/978-1-4666-2169-5.ch003
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MLA

Domingues, Miriam Lúcia, and Eloi Luiz Favero. "Domain Adaptation in Part-of-Speech Tagging." Emerging Applications of Natural Language Processing: Concepts and New Research, edited by Sivaji Bandyopadhyay, et al., IGI Global, 2013, pp. 52-72. https://doi.org/10.4018/978-1-4666-2169-5.ch003

APA

Domingues, M. L. & Favero, E. L. (2013). Domain Adaptation in Part-of-Speech Tagging. In S. Bandyopadhyay, S. Naskar, & A. Ekbal (Eds.), Emerging Applications of Natural Language Processing: Concepts and New Research (pp. 52-72). IGI Global. https://doi.org/10.4018/978-1-4666-2169-5.ch003

Chicago

Domingues, Miriam Lúcia, and Eloi Luiz Favero. "Domain Adaptation in Part-of-Speech Tagging." In Emerging Applications of Natural Language Processing: Concepts and New Research, edited by Sivaji Bandyopadhyay, Sudip Kumar Naskar, and Asif Ekbal, 52-72. Hershey, PA: IGI Global, 2013. https://doi.org/10.4018/978-1-4666-2169-5.ch003

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Abstract

Many Natural Language Processing (NLP) applications rely on accuracy of the part-of-speech taggers. Although many taggers have good accuracy for the domain in which they were trained, their accuracy typically is not portable to new domains due to problems, such as different linguistic structures or presence of new words. The need for domain adaptation has emerged as a new challenge for part-of-speech tagging and in most NLP tasks. The goal of this chapter is to highlight solutions that handle labeled and unlabeled data, methods that deal with such data to solve the domain adaptation problem, and to present a case study that has achieved significant accuracy rates on tagging journalistic and scientific texts.

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