A systematic review of NLP research on privacy policies finds heavy focus on text classification and sparse work on summarization, question answering, and alignment.
Open Domain Event Extraction Using Neural Latent Variable Models
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abstract
We consider open domain event extraction, the task of extracting unconstraint types of events from news clusters. A novel latent variable neural model is constructed, which is scalable to very large corpus. A dataset is collected and manually annotated, with task-specific evaluation metrics being designed. Results show that the proposed unsupervised model gives better performance compared to the state-of-the-art method for event schema induction.
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Natural Language Processing of Privacy Policies: A Survey
A systematic review of NLP research on privacy policies finds heavy focus on text classification and sparse work on summarization, question answering, and alignment.