• DocumentCode
    130336
  • Title

    Ladder tagger — Splitting decision space to boost tagging quality

  • Author

    Paradowski, Mariusz ; Radziszewski, Adam

  • Author_Institution
    Inst. of Inf., Wroclaw Univ. of Technol., Wroclaw, Poland
  • fYear
    2014
  • fDate
    7-10 Sept. 2014
  • Firstpage
    163
  • Lastpage
    169
  • Abstract
    This paper describes a part of speech tagger. The tagger is based on a set of probability mixture models. Each mixture model is responsible for tagging of a specific class of words, sharing similar context properties. Probability mixture models contain 25 various mixture components. The tagger is tested on Polish language and compared to other available taggers.
  • Keywords
    mixture models; natural language processing; probability; Polish language; decision space splitting; ladder tagger; probability mixture models; speech tagger; tagging quality; Context; Indexes; Mathematical model; Smoothing methods; Tagging; Training; Training data;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Science and Information Systems (FedCSIS), 2014 Federated Conference on
  • Conference_Location
    Warsaw
  • Type

    conf

  • DOI
    10.15439/2014F107
  • Filename
    6933009
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=130336