Supervised Word Sense Disambiguation with Sentences Similarities from Context Word Embeddings

@inproceedings{Yamaki2016SupervisedWS,
  title={Supervised Word Sense Disambiguation with Sentences Similarities from Context Word Embeddings},
  author={Shoma Yamaki and Hiroyuki Shinnou and Kanako Komiya and Minoru Sasaki},
  booktitle={PACLIC},
  year={2016}
}
In this paper, we propose a method that employs sentences similarities from context word embeddings for supervised word sense disambiguation. In particular, if N example sentences exist in training data, an N-dimensional vector with N similarities between each pair of example sentences is added to a basic feature vector. This new feature vector is used to train a classifier and identification. We evaluated the proposed method using the feature vectors based on Bag-of-Words, SemEval-2 baseline… CONTINUE READING

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