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Exploiting Syntax when Detecting Protein Names in Text
RISE, Swedish ICT, SICS.ORCID iD: 0000-0001-6949-6380
RISE, Swedish ICT, SICS.
RISE, Swedish ICT, SICS.
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2002 (English)In: Proceedings of FMI Workshop on Natural Language Processing in Biomedical Applications, 2002, 1, , p. 6Conference paper, Published paper (Refereed)
Abstract [en]

This paper presents work on a method to detect names of proteins in running text. Our system - Yapex - uses a combination of lexical and syntactic knowledge, heuristic filters and a local dynamic dictionary. The syntactic information given by a general-purpose off-the-shelf parser supports the correct identification of the boundaries of protein names, and the local dynamic dictionary finds protein names in positions incompletely analysed by the parser. We present the different steps involved in our approach to protein tagging, and show how combinations of them influence recall and precision. We evaluate the system on a corpus of MEDLINE abstracts and compare it with the KeX system (Fukuda et al., 1998) along four different notions of correctness.

Place, publisher, year, edition, pages
2002, 1. , p. 6
National Category
Computer and Information Sciences
Identifiers
URN: urn:nbn:se:ri:diva-22240OAI: oai:DiVA.org:ri-22240DiVA, id: diva2:1041785
Conference
EFMI Workshop on Natural Language Processing in Biomedical Applications, March 8-9, 2002, Nicosia, Cyprus
Available from: 2016-10-31 Created: 2016-10-31 Last updated: 2020-12-02Bibliographically approved

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fulltext(203 kB)102 downloads
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CiteExportLink to record
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Citation style
  • apa
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  • vancouver
  • Other style
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  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
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  • Other locale
More languages
Output format
  • html
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