Improving Distributed Representation of Word Sense via WordNet Gloss Composition and Context Clustering

@inproceedings{Chen2015ImprovingDR,
  title={Improving Distributed Representation of Word Sense via WordNet Gloss Composition and Context Clustering},
  author={Tao Chen and Ruifeng Xu and Yulan He and Xuan Wang},
  booktitle={ACL},
  year={2015}
}
In recent years, there has been an increasing interest in learning a distributed representation of word sense. Traditional context clustering based models usually require careful tuning of model parameters, and typically perform worse on infrequent word senses. This paper presents a novel approach which addresses these limitations by first initializing the word sense embeddings through learning sentencelevel embeddings from WordNet glosses using a convolutional neural networks. The initialized… CONTINUE READING

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Computational Linguistics and Intelligent Text Processing

  • Lecture Notes in Computer Science
  • 2017
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