Paper: Unsupervised Alignment of Privacy Policies using Hidden Markov Models

ACL ID P14-2099
Title Unsupervised Alignment of Privacy Policies using Hidden Markov Models
Venue Annual Meeting of the Association of Computational Linguistics
Session Main Conference
Year 2014
Authors

To support empirical study of online pri- vacy 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 clus- tering and topic models.