@inproceedings{dzendzik-etal-2019-dish,
title = "Is It Dish Washer Safe? Automatically Answering {``}Yes/No{''} Questions Using Customer Reviews",
author = "Dzendzik, Daria and
Vogel, Carl and
Foster, Jennifer",
editor = "Kar, Sudipta and
Nadeem, Farah and
Burdick, Laura and
Durrett, Greg and
Han, Na-Rae",
booktitle = "Proceedings of the 2019 Conference of the North {A}merican Chapter of the Association for Computational Linguistics: Student Research Workshop",
month = jun,
year = "2019",
address = "Minneapolis, Minnesota",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/N19-3001",
doi = "10.18653/v1/N19-3001",
pages = "1--6",
abstract = "It has become commonplace for people to share their opinions about all kinds of products by posting reviews online. It has also become commonplace for potential customers to do research about the quality and limitations of these products by posting questions online. We test the extent to which reviews are useful in question-answering by combining two Amazon datasets and focusing our attention on yes/no questions. A manual analysis of 400 cases reveals that the reviews directly contain the answer to the question just over a third of the time. Preliminary reading comprehension experiments with this dataset prove inconclusive, with accuracy in the range 50-66{\%}.",
}
Markdown (Informal)
[Is It Dish Washer Safe? Automatically Answering “Yes/No” Questions Using Customer Reviews](https://aclanthology.org/N19-3001) (Dzendzik et al., NAACL 2019)
ACL