Privacy Policy Question Answering Assistant: A Query-Guided Extractive
Summarization Approach
- URL: http://arxiv.org/abs/2109.14638v1
- Date: Wed, 29 Sep 2021 18:00:09 GMT
- Title: Privacy Policy Question Answering Assistant: A Query-Guided Extractive
Summarization Approach
- Authors: Moniba Keymanesh, Micha Elsner, Srinivasan Parthasarathy
- Abstract summary: We propose an automated privacy policy question answering assistant that extracts a summary in response to the input user query.
This is a challenging task because users articulate their privacy-related questions in a very different language than the legal language of the policy.
Our pipeline is able to find an answer for 89% of the user queries in the privacyQA dataset.
- Score: 18.51811191325837
- License: http://creativecommons.org/licenses/by/4.0/
- Abstract: Existing work on making privacy policies accessible has explored new
presentation forms such as color-coding based on the risk factors or
summarization to assist users with conscious agreement. To facilitate a more
personalized interaction with the policies, in this work, we propose an
automated privacy policy question answering assistant that extracts a summary
in response to the input user query. This is a challenging task because users
articulate their privacy-related questions in a very different language than
the legal language of the policy, making it difficult for the system to
understand their inquiry. Moreover, existing annotated data in this domain are
limited. We address these problems by paraphrasing to bring the style and
language of the user's question closer to the language of privacy policies. Our
content scoring module uses the existing in-domain data to find relevant
information in the policy and incorporates it in a summary. Our pipeline is
able to find an answer for 89% of the user queries in the privacyQA dataset.
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