Abstract
The paper addresses the problem of automatic enrichment of a thesaurus by classifying new words into its classes. The proposed classification method makes use of both the distributional data about a new word and the strength of the semantic relatedness of its target class to other likely candidate classes.
Cite
CITATION STYLE
APA
Pekar, V., & Staab, S. (2003). Word classification based on combined measures of distributional and semantic similarity. In 10th Conference of the European Chapter of the Association for Computational Linguistics, EACL 2003 (pp. 147–150). Association for Computational Linguistics (ACL). https://doi.org/10.3115/1067737.1067770
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