Papers with unsupervised corpus sense tagging

1 papers
Constructing High Quality Sense-specific Corpus and Word Embedding via Unsupervised Elimination of Pseudo Multi-sense (L18-1)

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Challenge: Existing word embedding frameworks distinguish different senses of words by their contexts.
Approach: They propose a framework for unsupervised corpus sense tagging which trains multi-sense word embeddings on a given corpus.
Outcome: The proposed framework detects pseudo multi-senses without extra language resources without additional language resources.

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