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Privacy Policy Question Answering Assistant: A Query-Guided Extractive Summarization Approach

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arxiv 2109.14638 v1 pith:QTJMAX3B submitted 2021-09-29 cs.CL cs.CYcs.IR

classification cs.CLcs.CYcs.IR
keywords languagepolicyprivacyexistingpoliciesquestionuseranswering
verification ladder T0 review T1 audit T2 compute T3 formal

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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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Cited by 1 Pith paper

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. SoK: From Generation to Consumption of Privacy Documents in Software Systems

    cs.CR 2026-08 conditional novelty 6.0 of 10

    A systematic review of 290 papers (2010 to 2025) organizes privacy-document research into a five-stage lifecycle and identifies 15 trends, 21 opportunities, and 4 research directions.

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