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Unsupervised Alignment of Privacy Policies using Hidden Markov Models

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journal contribution
posted on 01.06.2014, 00:00 by Rohan Ramanath, Fei Liu, Norman Sadeh-Koniecpol, Noah A. Smith

To support empirical study of online privacy policies, as well as tools for users with privacy concerns, we consider the problem of aligning sections of a thousand policy documents, based on the issues they address. We apply an unsupervised HMM; in two new (and reusable) evaluations, we find the approach more effective than clustering and topic models.

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Copyright 2014 Association for Computational Linguistics

Date

01/06/2014

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