Tailoring the automated construction of large-scale taxonomies using the web.

It has long been a dream to have available a single, centralized, semantic thesaurus or terminology taxonomy to support research in a variety of fields. Much human and computational effort has gone into constructing such resources, including the original WordNet and subsequent wordnets in various la...

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Publicado en:Language Resources & Evaluation Vol. 47; no. 3; pp. 859 - 891
Autores principales: Kozareva, Zornitsa, Hovy, Eduard
Formato: Artículo
Publicado: Springer Nature Sep2013
Materias:
Acceso en línea:Ver este registro en EBSCOhost
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          Kozareva, Zornitsa
          Hovy, Eduard
        affil: USC Information Sciences Institute, 4676 Admiralty Way Marina del Rey 90292-6695 USA
      su:
        Text mining
        Taxonomic logic
        Automation
        Language & languages
        Terms & phrases
        Ontology
      sug:
        subj:
          Text mining
          Taxonomic logic
          Automation
          Language & languages
          Terms & phrases
          Ontology
      keyword:
        Hyponym and hypernym learning
        Ontology induction
        Wordnet evaluation
      ab: It has long been a dream to have available a single, centralized, semantic thesaurus or terminology taxonomy to support research in a variety of fields. Much human and computational effort has gone into constructing such resources, including the original WordNet and subsequent wordnets in various languages. To produce such resources one has to overcome well-known problems in achieving both wide coverage and internal consistency within a single wordnet and across many wordnets. In particular, one has to ensure that alternative valid taxonomizations covering the same basic terms are recognized and treated appropriately. In this paper we describe a pipeline of new, powerful, minimally supervised, automated algorithms that can be used to construct terminology taxonomies and wordnets, in various languages, by harvesting large amounts of online domain-specific or general text. We illustrate the effectiveness of the algorithms both to build localized, domain-specific wordnets and to highlight and investigate certain deeper ontological problems such as parallel generalization hierarchies. We show shortcomings and gaps in the manually-constructed English WordNet in various domains.
      pubtype: Academic Journal
      doctype: Article
      src: R
    language: English
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      custom: Language Resources & Evaluation is a copyright of Springer, 2013. All Rights Reserved.
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