Papers with privacy policy

2 papers
Intent Classification and Slot Filling for Privacy Policies (2021.acl-long)

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Challenge: Sentences written in privacy policies explain privacy practices and the constituent text spans convey further specific information.
Approach: They propose an English corpus of 5,250 intent and 11,788 slot annotations . they propose two alternative neural approaches to model the corpus as a sequence-to-sequence learning task.
Outcome: The proposed corpus predicts intent classification and slot filling, while the sequence tagging method outperforms slot filler by a large margin.
Privacy at Scale: Introducing the PrivaSeer Corpus of Web Privacy Policies (2021.acl-long)

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Challenge: Existing tools to interpret privacy policies have been used to understand them but there is a lack of large privacy policy corpora to simplify the process.
Approach: They propose to use a corpus of 1,005,380 English language privacy policies collected from the web to create semi-supervised and unsupervised models to interpret and simplify privacy policies.
Outcome: The proposed model outperforms all other publicly available privacy policy corpora and is ten times larger than the next largest public collection of privacy policies combined.

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