An Iterative Approach for Unsupervised Most Frequent Sense Detection using WordNet and Word Embeddings
نویسنده
چکیده
Given a word, what is the most frequent sense in which it occurs in a given corpus? Most Frequent Sense (MFS) is a strong baseline for unsupervised word sense disambiguation. If we have large amounts of sense-annotated corpora, MFS can be trivially created. However, senseannotated corpora are a rarity. In this paper, we propose a method which can compute MFS from raw corpora. Our approach iteratively exploits the semantic congruity among related words in corpus. Our method performs better compared to another similar work.
منابع مشابه
Unsupervised Most Frequent Sense Detection using Word Embeddings
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