Abstract
This paper presents an unsupervised method for discriminating among the senses of a given target word based on the context in which it occurs. Instances of a word that occur in similar contexts are grouped together via McQuitty's Similarity Analysis, an agglomerative clustering algorithm. The context in which a target word occurs is represented by surface lexical features such as unigrams, bigrams, and second order co-occurrences. This paper summarizes our approach, and describes the results of a preliminary evaluation we have carried out using data from the SENSEVAL-2 English lexical sample and the line corpus.
Cite
CITATION STYLE
Purandare, A. (2003). Discriminating among word senses using McQuitty’s similarity analysis. In Proceedings of the 2003 Human Language Technology Conference of the North American Chapter of the Association for Computational Linguistics - Student Research Workshop, HLT-NAACL 2003 (pp. 19–24). Association for Computational Linguistics (ACL). https://doi.org/10.3115/1073416.1073420
Register to see more suggestions
Mendeley helps you to discover research relevant for your work.
