@inproceedings{haponchyk-etal-2018-supervised,
    title = "Supervised Clustering of Questions into Intents for Dialog System Applications",
    author = "Haponchyk, Iryna  and
      Uva, Antonio  and
      Yu, Seunghak  and
      Uryupina, Olga  and
      Moschitti, Alessandro",
    booktitle = "Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing",
    month = oct # "-" # nov,
    year = "2018",
    address = "Brussels, Belgium",
    publisher = "Association for Computational Linguistics",
    url = "https://aclanthology.org/D18-1254",
    doi = "10.18653/v1/D18-1254",
    pages = "2310--2321",
    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.",
}