Thesaurus or logical ontology, which one do we need for text mining?

    Research output: Contribution to journalArticlepeer-review

    Abstract

    Ontologies are recognised as important tools, not only for effective and efficient information sharing, but also for information extraction and text mining. In the biomedical domain, the need for a common ontology for information sharing has long been recognised, and several ontologies are now widely used. However, there is confusion among researchers concerning the type of ontology that is needed for text mining , and how it can be used for effective knowledge management, sharing, and integration in biomedicine. We argue that there are several different ways to define an ontology and that, while the logical view is popular for some applications, it may be neither possible nor necessary for text mining. We propose a text-centered approach for knowledge sharing, as an alternative to formal ontologies. We argue that a thesaurus (i.e. an organised collection of terms enriched with relations) is more useful for text mining applications than formal ontologies. © Springer 2005.
    Original languageEnglish
    Pages (from-to)77-90
    Number of pages13
    JournalLanguage Resources and Evaluation
    Volume39
    Issue number1
    DOIs
    Publication statusPublished - Feb 2005

    Keywords

    • Ontology
    • Terminology
    • Text mining
    • Thesaurus

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