Determining Gains Acquired from Word Embedding Quantitatively Using Discrete Distribution Clustering
Jianbo Ye, Yanran Li, Zhaohui Wu, James Z. Wang, Wenjie Li, Jia Li
Abstract
Word embeddings have become widely-used in document analysis. While a large number of models for mapping words to vector spaces have been developed, it remains undetermined how much net gain can be achieved over traditional approaches based on bag-of-words. In this paper, we propose a new document clustering approach by combining any word embedding with a state-of-the-art algorithm for clustering empirical distributions. By using the Wasserstein distance between distributions, the word-to-word semantic relationship is taken into account in a principled way. The new clustering method is easy to use and consistently outperforms other methods on a variety of data sets. More importantly, the method provides an effective framework for determining when and how much word embeddings contribute to document analysis. Experimental results with multiple embedding models are reported.- Anthology ID:
- P17-1169
- Volume:
- Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
- Month:
- July
- Year:
- 2017
- Address:
- Vancouver, Canada
- Venue:
- ACL
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 1847–1856
- Language:
- URL:
- https://aclanthology.org/P17-1169
- DOI:
- 10.18653/v1/P17-1169
- Cite (ACL):
- Jianbo Ye, Yanran Li, Zhaohui Wu, James Z. Wang, Wenjie Li, and Jia Li. 2017. Determining Gains Acquired from Word Embedding Quantitatively Using Discrete Distribution Clustering. In Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), pages 1847–1856, Vancouver, Canada. Association for Computational Linguistics.
- Cite (Informal):
- Determining Gains Acquired from Word Embedding Quantitatively Using Discrete Distribution Clustering (Ye et al., ACL 2017)
- PDF:
- https://preview.aclanthology.org/ingestion-script-update/P17-1169.pdf