04/07/2020

Unsupervised FAQ Retrieval with Question Generation and BERT

Yosi Mass, Boaz Carmeli, Haggai Roitman, David Konopnicki

Keywords: Unsupervised Retrieval, Question Generation, Frequently retrieval, fully method

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.

 0
 0
 0
 0
This is an embedded video. Talk and the respective paper are published at ACL 2020 virtual conference. If you are one of the authors of the paper and want to manage your upload, see the question "My papertalk has been externally embedded..." in the FAQ section.

Comments

Post Comment
no comments yet
code of conduct: tbd Characters remaining: 140

Similar Papers