@inproceedings{mass-etal-2020-unsupervised,
    title = "Unsupervised {FAQ} Retrieval with Question Generation and {BERT}",
    author = "Mass, Yosi  and
      Carmeli, Boaz  and
      Roitman, Haggai  and
      Konopnicki, David",
    editor = "Jurafsky, Dan  and
      Chai, Joyce  and
      Schluter, Natalie  and
      Tetreault, Joel",
    booktitle = "Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics",
    month = jul,
    year = "2020",
    address = "Online",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/jlcl-multiple-ingestion/2020.acl-main.74/",
    doi = "10.18653/v1/2020.acl-main.74",
    pages = "807--812",
    abstract = "We focus on the task of Frequently Asked Questions (FAQ) retrieval. A given user query can be matched against the questions and/or the answers in the FAQ. We present a fully unsupervised method that exploits the FAQ pairs to train two BERT models. The two models match user queries to FAQ answers and questions, respectively. We alleviate the missing labeled data of the latter by automatically generating high-quality question paraphrases. We show that our model is on par and even outperforms supervised models on existing datasets."
}