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Using linguistic information to improve the performance of vector-based semantic analysis
Number of Authors: 2
2001 (English)Conference paper, (Refereed)
Abstract [en]

The use of vector-based models of information for the purpose of semantic analysis is an area of research that has gained substantial recognition over the last decade. However, the application of high-dimensional vector representations to linguistic data has, to a large extent, remained exclusively statistical and consequently paid minimal or no attention to the linguistic structures of the data used in the experiments. In this paper, we show that the performance of vector based semantic analysis can be improved by considering basic linguistic structures - e.g. morphology - in the data.

Place, publisher, year, edition, pages
2001, 1.
National Category
Computer and Information Science
Identifiers
URN: urn:nbn:se:ri:diva-22657OAI: oai:DiVA.org:ri-22657DiVA: diva2:1042222
Conference
NoDaLiDa '01: 13th Nordic Conference on Computational Linguistics
Available from: 2016-10-31 Created: 2016-10-31Bibliographically approved

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Permanent link

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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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