A Unified Approach to Word Sense Representation and Disambiguation

Do Myoung Lee, Yeachan Kim, Ji Min Lee, Sang-Geun Lee

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

The lexical ambiguity of words has been successfully clarified by representing words at a sense level instead of a word level. This is known as word sense representation (WSR). However, WSR models are typically trained in an unsupervised fashion without any guidance from sense inventories. Therefore, the number of sense vectors assigned to a word varies from model to model. This implies that some senses are missed or unnecessarily added. Moreover, to utilize their sense vectors in natural language processing tasks, we must determine which sense of a word to choose. In this paper, we introduce a unified neural model that incorporates WSR into word sense disambiguation (WSD), thereby leveraging the sense inventory. We use bidirectional long short-term memory networks to capture the sequential information of contexts effectively. To overcome the limitation of size with the labeled dataset, we train our model in a semi-supervised fashion to scale up the size of the dataset by leveraging a large-scale unlabeled dataset. We evaluate our proposed model on both WSR and WSD tasks. The experimental results demonstrate that our model outperforms state-of-the-art on WSR task by 0.27%, while, on WSD task, by 1.4% in terms of Spearman's correlation and F'l-score, respectively.

Original languageEnglish
Title of host publicationProceedings of 2018 IEEE 17th International Conference on Cognitive Informatics and Cognitive Computing, ICCI*CC 2018
EditorsNewton Howard, Sam Kwong, Yingxu Wang, Jerome Feldman, Bernard Widrow, Phillip Sheu
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages330-336
Number of pages7
ISBN (Electronic)9781538633601
DOIs
Publication statusPublished - 2018 Oct 4
Event17th IEEE International Conference on Cognitive Informatics and Cognitive Computing, ICCI*CC 2018 - Berkeley, United States
Duration: 2018 Jul 162018 Jul 18

Other

Other17th IEEE International Conference on Cognitive Informatics and Cognitive Computing, ICCI*CC 2018
CountryUnited States
CityBerkeley
Period18/7/1618/7/18

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Keywords

  • Artificial neural nets
  • Computational Intelligence
  • Natural language processing
  • Recurrent neural networks

ASJC Scopus subject areas

  • Artificial Intelligence
  • Information Systems
  • Cognitive Neuroscience

Cite this

Lee, D. M., Kim, Y., Lee, J. M., & Lee, S-G. (2018). A Unified Approach to Word Sense Representation and Disambiguation. In N. Howard, S. Kwong, Y. Wang, J. Feldman, B. Widrow, & P. Sheu (Eds.), Proceedings of 2018 IEEE 17th International Conference on Cognitive Informatics and Cognitive Computing, ICCI*CC 2018 (pp. 330-336). [8482041] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICCI-CC.2018.8482041