Efficient Graph-based Word Sense Induction by Distributional Inclusion Vector Embeddings
Haw-Shiuan Chang, Amol Agrawal, Ananya Ganesh, Anirudha Desai, Vinayak Mathur, Alfred Hough, Andrew McCallum
Abstract
Word sense induction (WSI), which addresses polysemy by unsupervised discovery of multiple word senses, resolves ambiguities for downstream NLP tasks and also makes word representations more interpretable. This paper proposes an accurate and efficient graph-based method for WSI that builds a global non-negative vector embedding basis (which are interpretable like topics) and clusters the basis indexes in the ego network of each polysemous word. By adopting distributional inclusion vector embeddings as our basis formation model, we avoid the expensive step of nearest neighbor search that plagues other graph-based methods without sacrificing the quality of sense clusters. Experiments on three datasets show that our proposed method produces similar or better sense clusters and embeddings compared with previous state-of-the-art methods while being significantly more efficient.- Anthology ID:
- W18-1706
- Volume:
- Proceedings of the Twelfth Workshop on Graph-Based Methods for Natural Language Processing (TextGraphs-12)
- Month:
- June
- Year:
- 2018
- Address:
- New Orleans, Louisiana, USA
- Editors:
- Goran Glavaš, Swapna Somasundaran, Martin Riedl, Eduard Hovy
- Venue:
- TextGraphs
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 38–48
- Language:
- URL:
- https://aclanthology.org/W18-1706
- DOI:
- 10.18653/v1/W18-1706
- Cite (ACL):
- Haw-Shiuan Chang, Amol Agrawal, Ananya Ganesh, Anirudha Desai, Vinayak Mathur, Alfred Hough, and Andrew McCallum. 2018. Efficient Graph-based Word Sense Induction by Distributional Inclusion Vector Embeddings. In Proceedings of the Twelfth Workshop on Graph-Based Methods for Natural Language Processing (TextGraphs-12), pages 38–48, New Orleans, Louisiana, USA. Association for Computational Linguistics.
- Cite (Informal):
- Efficient Graph-based Word Sense Induction by Distributional Inclusion Vector Embeddings (Chang et al., TextGraphs 2018)
- PDF:
- https://preview.aclanthology.org/ingest-acl-2023-videos/W18-1706.pdf