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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 authored by Rohan Ramanath, Fei Liu, Norman SadehNorman Sadeh, 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



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