Unsupervised Linguistically-Driven Reliable Dependency Parses Detection and Self-Training for Adaptation to the Biomedical Domain (Contributo in atti di convegno)

Type
Label
  • Unsupervised Linguistically-Driven Reliable Dependency Parses Detection and Self-Training for Adaptation to the Biomedical Domain (Contributo in atti di convegno) (literal)
Anno
  • 2013-01-01T00:00:00+01:00 (literal)
Alternative label
  • Felice Dell'Orletta, Giulia Venturi, Simonetta Montemagni (2013)
    Unsupervised Linguistically-Driven Reliable Dependency Parses Detection and Self-Training for Adaptation to the Biomedical Domain
    in 12th workshop on "Biomedical Natural Language Processing" (BioNLP), Sofia (Bulgaria), 8-9 agosto 2013
    (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#autori
  • Felice Dell'Orletta, Giulia Venturi, Simonetta Montemagni (literal)
Pagina inizio
  • 45 (literal)
Pagina fine
  • 53 (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#url
  • http://www.aclweb.org/anthology/W13-1906 (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#affiliazioni
  • ILC - Istituto di linguistica computazionale \"Antonio Zampolli\" (literal)
Titolo
  • Unsupervised Linguistically-Driven Reliable Dependency Parses Detection and Self-Training for Adaptation to the Biomedical Domain (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#isbn
  • 978-1-937284-55-8 (literal)
Abstract
  • In this paper, a new self-training method for domain adaptation is illustrated, where the selection of reliable parses is carried out by an unsupervised linguistically-driven algorithm, ULISSE. The method has been tested on biomedical texts with results showing a significant improvement with respect to considered baselines, which demonstrates its ability to capture both reliability of parses and domain-specificity of linguistic constructions. (literal)
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