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Crowdsourcing Annotations for Websites' Privacy Policies: Can It Really Work?

, , , , , , и . WWW, стр. 133-143. ACM, (2016)

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Sreenath Ramanath

Rohan Karande

Ali Reza Rohani-Dezfuli

Massoud Rohani

Rohan Karande

 

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An Attentive Survey of Attention Models., , , и . CoRR, (2019)Entailment: An Effective Metric for Comparing and Evaluating Hierarchical and Non-hierarchical Annotation Schemes., , и . LAW@ACL, стр. 42-50. The Association for Computer Linguistics, (2013)Efficient Algorithms for Global Inference in Internet Marketplaces., , , , и . CoRR, (2021)Lambda Learner: Fast Incremental Learning on Data Streams., , , , , , , и . KDD, стр. 3492-3502. ACM, (2021)Analyzing Privacy Policies at Scale: From Crowdsourcing to Automated Annotations., , , , , , , , , и 1 other автор(ы). ACM Trans. Web, 13 (1): 1:1-1:29 (2019)Logit Attenuating Weight Normalization., , , , , , и . CoRR, (2021)Unsupervised Alignment of Privacy Policies using Hidden Markov Models., , , и . ACL (2), стр. 605-610. The Association for Computer Linguistics, (2014)Lambda Learner: Fast Incremental Learning on Data Streams., , , , , , , и . CoRR, (2020)Crowd Prefers the Middle Path: A New IAA Metric for Crowdsourcing Reveals Turker Biases in Query Segmentation., , , и . ACL (1), стр. 1713-1722. The Association for Computer Linguistics, (2013)An Attentive Survey of Attention Models., , , и . ACM Trans. Intell. Syst. Technol., 12 (5): 53:1-53:32 (2021)