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<Paper uid="P06-2119">
  <Title>Word Sense Disambiguation using lexical cohesion in the context</Title>
  <Section position="9" start_page="935" end_page="935" type="concl">
    <SectionTitle>
8 Conclusion and future work
</SectionTitle>
    <Paragraph position="0"> In this paper we defined the lexical hub and proposed its use for processing word sense disambiguation, achieving results that are comparatively better than most unsupervised systems of SENSEVAL-2 in the literature. Since WordNet only organizes the paradigmatic relations of words, unlike previous methods, which are only based on WordNet, we fed the syntagmatic relations of words from the EAT into the noun and verb similarity metrics, and significantly improved the results of WSD, given that no back-off was applied. Moreover, we only utilized the unordered raw context information without any pragmatic knowledge and syntactic information; there is still a lot of work to fuse them in the future research. In terms of the heuristics evaluated, richness of sense or word connectivity is much more important than the strength of individual word or sense linkages. An interesting question is whether these results will be borne out in other datasets. In the forthcoming work we will investigate their validity in the lexical task of SENSEVAL-3. null</Paragraph>
  </Section>
class="xml-element"></Paper>