Papers by Mikhail Chernoskutov

1 papers
An Unsupervised Word Sense Disambiguation System for Under-Resourced Languages (L18-1)

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Challenge: Existing systems for word sense disambiguation are limited to the Russian language and lack of resources to address the problem.
Approach: They propose an unsupervised system for word sense disambiguation that uses a traditional vector space model to estimate the most similar word sense corresponding to its context.
Outcome: The proposed system outperforms the sparse mode on all datasets according to the adjusted Rand index.

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