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Description
  • This paper compares two techniques for robust parsing of extra-grammatical natural language that might be of interest in large scale Textual Data Analysis applications. The first one returns a "correct" derivation for any extra-grammatical sentence by generating the finest corresponding most probable optimal maximum coverage. The second one extends the initial grammar by adding relaxed grammar rules in a controlled manner. Both techniques use a stochastic parser that selects a "best" solution among multiple analyses. The techniques were tested on the ATIS and Susanne corp ora and exp erimental results, as well as conclusions on performance comparison, are provided.
  • This paper compares two techniques for robust parsing of extra-grammatical natural language that might be of interest in large scale Textual Data Analysis applications. The first one returns a "correct" derivation for any extra-grammatical sentence by generating the finest corresponding most probable optimal maximum coverage. The second one extends the initial grammar by adding relaxed grammar rules in a controlled manner. Both techniques use a stochastic parser that selects a "best" solution among multiple analyses. The techniques were tested on the ATIS and Susanne corp ora and exp erimental results, as well as conclusions on performance comparison, are provided. (en)
Title
  • Efficient Processing of Extra-grammatical Sentences: Comparing and Combining two approaches to Robust Stochastic Parsing
  • Efficient Processing of Extra-grammatical Sentences: Comparing and Combining two approaches to Robust Stochastic Parsing (en)
skos:prefLabel
  • Efficient Processing of Extra-grammatical Sentences: Comparing and Combining two approaches to Robust Stochastic Parsing
  • Efficient Processing of Extra-grammatical Sentences: Comparing and Combining two approaches to Robust Stochastic Parsing (en)
skos:notation
  • RIV/00216224:14330/05:00012485!RIV10-GA0-14330___
http://linked.open...avai/riv/aktivita
http://linked.open...avai/riv/aktivity
  • P(1ET100300414), P(GA201/05/2781)
http://linked.open...vai/riv/dodaniDat
http://linked.open...aciTvurceVysledku
http://linked.open.../riv/druhVysledku
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  • 519666
http://linked.open...ai/riv/idVysledku
  • RIV/00216224:14330/05:00012485
http://linked.open...riv/jazykVysledku
http://linked.open.../riv/klicovaSlova
  • robust; parsing; coverage (en)
http://linked.open.../riv/klicoveSlovo
http://linked.open...ontrolniKodProRIV
  • [4728528D9DCF]
http://linked.open...v/mistoKonaniAkce
  • Brest, Francie
http://linked.open...i/riv/mistoVydani
  • Francie
http://linked.open...i/riv/nazevZdroje
  • Proceedings of the Applied Stochastic Models and Data Analysis (ASMDA) 2005
http://linked.open...in/vavai/riv/obor
http://linked.open...ichTvurcuVysledku
http://linked.open...cetTvurcuVysledku
http://linked.open...vavai/riv/projekt
http://linked.open...UplatneniVysledku
http://linked.open...iv/tvurceVysledku
  • Kadlec, Vladimír
  • Rajman, Martin
  • Ailomaa, Marita
  • Chappelier, Jean-Cédric
http://linked.open...vavai/riv/typAkce
http://linked.open.../riv/zahajeniAkce
number of pages
http://purl.org/ne...btex#hasPublisher
  • ENST Bretagne
https://schema.org/isbn
  • 2-908849-15-1
http://localhost/t...ganizacniJednotka
  • 14330
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