Domain Adaptation for Word Sense Disambiguation Using Word Embeddings

In this paper, we propose domain adaptation in word sense disambiguation (WSD) using word embeddings. The validity of the word embeddings from a huge corpus, e.g., Wikipedia, for WSD had already been shown, but their validity in a domain adaptation framework has not been discussed before. In addition, if they are valid, the difference in effects according to the domain of the corpora is still unknown. Therefore, we investigate the performances of domain adaptation in WSD using the word embeddings from the source, target, and general corpora and examine (1) whether the word embeddings are valid for domain adaptation of WSD and (2) if they are, the effects in accordance with the domain of the corpora. The experiments using Japanese corpora revealed that the accuracy of WSD was highest when we used the word embeddings obtained from the target corpus.