Abstract
We introduce the dialog intent induction task and present a novel deep multi-view clustering approach to tackle the problem. Dialog intent induction aims at discovering user intents from user query utterances in human-human conversations such as dialogs between customer support agents and customers. Motivated by the intuition that a dialog intent is not only expressed in the user query utterance but also captured in the rest of the dialog, we split a conversation into two independent views and exploit multi-view clustering techniques for inducing the dialog intent. In par- ticular, we propose alternating-view k-means (AV-KMEANS) for joint multi-view represen- tation learning and clustering analysis. The key innovation is that the instance-view representations are updated iteratively by predicting the cluster assignment obtained from the alternative view, so that the multi-view representations of the instances lead to similar cluster assignments. Experiments on two public datasets show that AV-KMEANS can induce better dialog intent clusters than state-of-the-art unsupervised representation learning methods and standard multi-view clustering approaches.- Anthology ID:
- D19-1413
- Volume:
- Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP)
- Month:
- November
- Year:
- 2019
- Address:
- Hong Kong, China
- Editors:
- Kentaro Inui, Jing Jiang, Vincent Ng, Xiaojun Wan
- Venues:
- EMNLP | IJCNLP
- SIG:
- SIGDAT
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 4016–4025
- Language:
- URL:
- https://aclanthology.org/D19-1413
- DOI:
- 10.18653/v1/D19-1413
- Cite (ACL):
- Hugh Perkins and Yi Yang. 2019. Dialog Intent Induction with Deep Multi-View Clustering. In Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP), pages 4016–4025, Hong Kong, China. Association for Computational Linguistics.
- Cite (Informal):
- Dialog Intent Induction with Deep Multi-View Clustering (Perkins & Yang, EMNLP-IJCNLP 2019)
- PDF:
- https://preview.aclanthology.org/fix-dup-bibkey/D19-1413.pdf
- Code
- asappresearch/dialog-intent-induction