Calpric: Inclusive and Fine-grain Labeling of Privacy Policies with Crowdsourcing and Active Learning

arXiv:2008.02954 · cs.CR, cs.CL, cs.LG · Submitted 2020-08-07 · Read on arXiv

cs.CR, cs.CL, cs.LG

Submitted: 2020-08-07

Updated: 2026-09-19

Code: https://github.com/Mimino666/langdetect

Terminology

• Active Learning — 78× in this paper · explained in 6 episodes
• Accuracy — 35× in this paper · explained in 1 episode
• F1 Score — 15× in this paper · explained in 3 episodes
• Alignment — 8× in this paper · explained in 1 episode
• Acceptance Threshold — 4× in this paper
• Alignment Rate — 4× in this paper
• Embeddings — 4× in this paper · explained in 2 episodes
• Adam — 3× in this paper · explained in 2 episodes
• Expected Error Reduction — 3× in this paper
• Incremental Re-Labeling — 3× in this paper
• Similarity Distance — 3× in this paper
• Agreement Percentage — 2× in this paper
• Batch Mode Uncertainty — 2× in this paper
• Entropy-based Sampling — 2× in this paper
• Generalization — 2× in this paper · explained in 13 episodes
• Information Density — 2× in this paper
• International Conference on Machine Learning — 2× in this paper
• Least Confidence — 2× in this paper
• Margin Sampling — 2× in this paper
• Matthew Correlation Coefficient — 2× in this paper
• Representation Learning — 2× in this paper · explained in 2 episodes
• Activation Function — 1× in this paper · explained in 1 episode
• Analyzer — 1× in this paper · explained in 1 episode
• Consistency — 1× in this paper · explained in 3 episodes
• Convolutional Neural Network — 1× in this paper
• Cosine Similarity — 1× in this paper · explained in 3 episodes
• Crowdsourcing Privacy Policy Segments — 1× in this paper
• Initial Data — 1× in this paper · explained in 2 episodes
• L ABELING E FFORT — 1× in this paper
• Logistic Regression — 1× in this paper
• Percentile Scores — 1× in this paper
• Perplexity — 1× in this paper · explained in 3 episodes
• Segment Threshold — 1× in this paper
• Selection Bias — 1× in this paper · explained in 4 episodes
• Training Effort Percentage — 1× in this paper
• Transfer Learning — 1× in this paper · explained in 10 episodes
• Transformer — 1× in this paper · explained in 2 episodes
• Vector Representations — 1× in this paper · explained in 2 episodes

Sources

• Deep Bayesian Active Learning with Image Data
• Polisis: Automated Analysis and Presentation of Privacy Policies Using Deep Learning
• Adam: A Method for Stochastic Optimization
• Recurrent Neural Network for Text Classification with Multi-Task Learning
• Active Discriminative Text Representation Learning

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