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Using heuristics, syntax and a local dynamic dictionary for protein name tagging
RISE, Swedish ICT, SICS. HUMLE.
Number of Authors: 3
2002 (English)Conference paper, Published paper (Refereed)
Abstract [en]

This paper presents work on a method to detect names of proteins in running text. The detection and categorisation of named entities, such as names of people, organisations and places, in classical MUC-style information extraction tasks (Borthwick 1998) might be regarded a solved problem. But names of proteins present a slightly different challenge because of their variant structural characteristics and the specifics of the text domains in which they appear. This certainly holds true for other biological substances, and probably for many other kinds of terminology as well. We will present the different steps involved in our approach to this problem, and show how combinations of them influence recall and precision.

Place, publisher, year, edition, pages
2002, 5.
National Category
Computer and Information Science
Identifiers
URN: urn:nbn:se:ri:diva-22511OAI: oai:DiVA.org:ri-22511DiVA: diva2:1042076
Conference
Proceedings of the second international conference on Human Language Technology Research
Available from: 2016-10-31 Created: 2016-10-31Bibliographically approved

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CiteExportLink to record
Permanent link

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Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
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