Flexible or Strict Taxonomic Organization? Impact on culturally-specific knowledge transfer

Fumiko Kano Glückstad, Morten Mørup

    Research output: Chapter in Book/Report/Conference proceedingArticle in proceedingsResearchpeer-review

    Abstract

    This work compares methods for constructing feature-based ontologies that are supposed to be used for culturally-specific knowledge transfer. The methods to be compared are the Terminological Ontology (TO) [1], a method of constructing ontology based on strict principles and rules, and the Infinite Relational Model (IRM) [2], a novel unsupervised machine learning method that learns multi-dimensional relations among concepts and features from loosely structured datasets. These methods are combined with a novel cognitive model, the Bayesian Model of Generalization (BMG) [3] that maps culturally-specific concepts existing in two cultures in an effective and intuitive manner.
    Original languageEnglish
    Title of host publicationProceedings of the 10th Terminology and Knowledge Engineering Conference (TKE 2012)
    Publication date2012
    Pages65-80
    Publication statusPublished - 2012
    Event10th Terminology and Knowledge Engineering Conference (TKE 2012) - Madrid, Spain
    Duration: 19 Jun 201222 Jun 2012
    http://www.oeg-upm.net/tke2012

    Conference

    Conference10th Terminology and Knowledge Engineering Conference (TKE 2012)
    CountrySpain
    CityMadrid
    Period19/06/201222/06/2012
    Internet address

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