Abstract
The positive effect of adding subword information to word embeddings has been demonstrated for predictive models. In this paper we investigate whether similar benefits can also be derived from incorporating subwords into counting models. We evaluate the impact of different types of subwords (n-grams and unsupervised morphemes), with results confirming the importance of subword information in learning representations of rare and out-of-vocabulary words.- Anthology ID:
- W18-1209
- Volume:
- Proceedings of the Second Workshop on Subword/Character LEvel Models
- Month:
- June
- Year:
- 2018
- Address:
- New Orleans
- Venue:
- SCLeM
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 66–71
- Language:
- URL:
- https://aclanthology.org/W18-1209
- DOI:
- 10.18653/v1/W18-1209
- Cite (ACL):
- Alexandre Salle and Aline Villavicencio. 2018. Incorporating Subword Information into Matrix Factorization Word Embeddings. In Proceedings of the Second Workshop on Subword/Character LEvel Models, pages 66–71, New Orleans. Association for Computational Linguistics.
- Cite (Informal):
- Incorporating Subword Information into Matrix Factorization Word Embeddings (Salle & Villavicencio, SCLeM 2018)
- PDF:
- https://preview.aclanthology.org/ingestion-script-update/W18-1209.pdf
- Code
- alexandres/lexvec