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<Paper uid="W03-1303">
  <Title>Using Domain-Specific Verbs for Term Classification</Title>
  <Section position="8" start_page="4" end_page="4" type="concl">
    <SectionTitle>
6 Conclusion
</SectionTitle>
    <Paragraph position="0"> Efficient update of the existing knowledge repositories in many rapidly expanding domains is a burning issue. Due to an enormous number of terms and the complex structure of the terminology, manual update approaches are prone to be both inefficient and inconsistent. Thus, it has become absolutely essential to implement efficient and reliable term recognition and term classification methods as means of maintaining the knowledge repositories. In this paper, we have suggested a domain independent classification method as a way of incorporating automatically recognised terms into an existing ontology. For the preliminary experiments, we used the UMLS ontology in the domain of biomedicine, but the method can be easily adapted to use other ontologies in any other domain.</Paragraph>
    <Paragraph position="1"> The classification method makes use of the contextual information. Not all word types found in the context are of equal importance in the process of reasoning about the terms: the most informative are verbs, noun phrases (especially terms) and adjectives. The presented term classification approach revolves around domain-specific verbs. These verbs are used to collect unclassified terms and to suggest their potential classes based on the automatically learnt verb complementation patterns.</Paragraph>
    <Paragraph position="2"> Note that not every term appearing in a corpus is guaranteed to be classified by the proposed classification method due to the fact that a term need not occur as a complement of a domain-specific verb. Still, for a large number of terms the classification method is expected to obtain the classification information, as it is highly probable (though not certain) for a term to occur in a context of a domain-specific verb. The main goal of the method is to provide aid for the automatic ontology update by populating newly recognised terms into an existing ontology, rather than classifying arbitrary term occurrences in the corpus.</Paragraph>
    <Paragraph position="3"> The presented classification method can be easily modified to use lexical classes other than verbs as a criterion for classification. Even more, it can be further generalised to use a combination of lexical classes, which can be specified as a set of lexico-syntactic patterns. Further experiments with the generalisation of the classification method by basing it on a set of domain-specific lexico-syntactic patterns instead of domain-specific verbs are expected to demonstrate better performance in terms of recall and precision. These facts suggest that our classification approach, in combination with the C/NC-value method, could be reliably used as a (semi)automatic ontology maintenance procedure.</Paragraph>
  </Section>
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