Abstract
In this article, we propose Fuzzy Hindi WordNet, which is an extended version of Hindi WordNet. The proposed idea of fuzzy relations and their role in modeling Fuzzy Hindi WordNet is explained. We mathematically define fuzzy relations and the composition of these fuzzy relations for this extended version. We show that the concept of composition of fuzzy relations can be used to infer a relation between two words that otherwise are not directly related in Hindi WordNet. Then we propose fuzzy graph connectivity measures that include both local and global measures. These measures are used in determining the significance of a concept (which is represented as a vertex in the fuzzy graph) in a specific context. Finally, we show how these extended measures solve the problem of word sense disambiguation (WSD) effectively, which is useful in many natural language processing applications to improve their performance. Experiments on standard sense tagged corpus for WSD show better results when Fuzzy Hindi WordNet is used in place of Hindi WordNet.
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