• DocumentCode
    1662602
  • Title

    When You Doubt, Abstain: From Misclassification to Epoché in Automatic Text Categorisation

  • Author

    Locoro, Angela ; Grignani, Daniele ; Mascardi, Viviana

  • Author_Institution
    Comput. Sci. Dept., Univ. of Genova, Genova, Italy
  • Volume
    3
  • fYear
    2011
  • Firstpage
    209
  • Lastpage
    212
  • Abstract
    This paper describes how natural language processing and ontologies are exploited for automatic text categorisation. The approach introduced is part of the MANENT system, an infrastructure for integrating, structuring and searching Digital Libraries. The procedure of structural information extraction, and of the automatic classification of the records according to natural language understanding and the WordNet Domains taxonomy is discussed. A comparison between two versions of the classification algorithm is conducted and the improvements of the new approach are articulated. In particular, using semantic connections between words refines the classification results while reducing misclassification to no classification.
  • Keywords
    classification; digital libraries; information retrieval; natural language processing; ontologies (artificial intelligence); text analysis; MANENT system; WordNet domain taxonomy; automatic text categorisation; digital libraries; natural language processing; natural language understanding; ontologies; record automatic classification; structural information extraction; Educational institutions; Frequency domain analysis; Humans; Libraries; Ontologies; Semantics; Tagging; automatic text categorisation; natural language processing; semantic digital libraries; wordnet domains;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Web Intelligence and Intelligent Agent Technology (WI-IAT), 2011 IEEE/WIC/ACM International Conference on
  • Conference_Location
    Lyon
  • Print_ISBN
    978-1-4577-1373-6
  • Electronic_ISBN
    978-0-7695-4513-4
  • Type

    conf

  • DOI
    10.1109/WI-IAT.2011.65
  • Filename
    6040842