A Computational Study on Word Meanings and Their Distributed Representations via Polymodal Embedding
Abstract
A distributed representation has become a popular approach to capturing a word meaning. Besides its success and practical value, however, questions arise about the relationships between a true word meaning and its distributed representation. In this paper, we examine such a relationship via polymodal embedding approach inspired by the theory that humans tend to use diverse sources in developing a word meaning. The result suggests that the existing embeddings lack in capturing certain aspects of word meanings which can be significantly improved by the polymodal approach. Also, we show distinct characteristics of different types of words (e.g. concreteness) via computational studies. Finally, we show our proposed embedding method outperforms the baselines in the word similarity measure tasks and the hypernym prediction tasks.- Anthology ID:
- I17-1022
- Volume:
- Proceedings of the Eighth International Joint Conference on Natural Language Processing (Volume 1: Long Papers)
- Month:
- November
- Year:
- 2017
- Address:
- Taipei, Taiwan
- Editors:
- Greg Kondrak, Taro Watanabe
- Venue:
- IJCNLP
- SIG:
- Publisher:
- Asian Federation of Natural Language Processing
- Note:
- Pages:
- 214–223
- Language:
- URL:
- https://aclanthology.org/I17-1022
- DOI:
- Cite (ACL):
- Joohee Park and Sung-hyon Myaeng. 2017. A Computational Study on Word Meanings and Their Distributed Representations via Polymodal Embedding. In Proceedings of the Eighth International Joint Conference on Natural Language Processing (Volume 1: Long Papers), pages 214–223, Taipei, Taiwan. Asian Federation of Natural Language Processing.
- Cite (Informal):
- A Computational Study on Word Meanings and Their Distributed Representations via Polymodal Embedding (Park & Myaeng, IJCNLP 2017)
- PDF:
- https://preview.aclanthology.org/emnlp-22-attachments/I17-1022.pdf
- Data
- HyperLex