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Graph-based Centrality Algorithms for Unsupervised Word Sense Disambiguation

Description: This thesis introduces an innovative methodology of combining some traditional dictionary based approaches to word sense disambiguation (semantic similarity measures and overlap of word glosses, both based on WordNet) with some graph-based centrality methods, namely the degree of the vertices, Pagerank, closeness, and betweenness. The approach is completely unsupervised, and is based on creating graphs for the words to be disambiguated. We experiment with several possible combinations of the se… more
Date: December 2008
Creator: Sinha, Ravi Som
Partner: UNT Libraries
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