Supervised Clustering of Questions into Intents for Dialog System Applications
Iryna Haponchyk, Antonio Uva, Seunghak Yu, Olga Uryupina, Alessandro Moschitti
Abstract
Modern automated dialog systems require complex dialog managers able to deal with user intent triggered by high-level semantic questions. In this paper, we propose a model for automatically clustering questions into user intents to help the design tasks. Since questions are short texts, uncovering their semantics to group them together can be very challenging. We approach the problem by using powerful semantic classifiers from question duplicate/matching research along with a novel idea of supervised clustering methods based on structured output. We test our approach on two intent clustering corpora, showing an impressive improvement over previous methods for two languages/domains.- Anthology ID:
- D18-1254
- Volume:
- Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing
- Month:
- October-November
- Year:
- 2018
- Address:
- Brussels, Belgium
- Editors:
- Ellen Riloff, David Chiang, Julia Hockenmaier, Jun’ichi Tsujii
- Venue:
- EMNLP
- SIG:
- SIGDAT
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 2310–2321
- Language:
- URL:
- https://aclanthology.org/D18-1254
- DOI:
- 10.18653/v1/D18-1254
- Cite (ACL):
- Iryna Haponchyk, Antonio Uva, Seunghak Yu, Olga Uryupina, and Alessandro Moschitti. 2018. Supervised Clustering of Questions into Intents for Dialog System Applications. In Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing, pages 2310–2321, Brussels, Belgium. Association for Computational Linguistics.
- Cite (Informal):
- Supervised Clustering of Questions into Intents for Dialog System Applications (Haponchyk et al., EMNLP 2018)
- PDF:
- https://preview.aclanthology.org/improve-issue-templates/D18-1254.pdf