Crowdsourcing infers ground truth from multiple annotators, verified for supervised learning.
arXiv research
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A framework for faster, better infographic design by non-experts and experts alike.
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A popular approach for large scale data annotation tasks is crowdsourcing, wherein each data point is labeled by multiple noisy annotators. We consider the problem of inferring ground truth from noisy ordinal labels obtained from multiple annotators of varying and unknown expertise levels. Annotation models for ordinal…
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Proposes a method for time-evolving and difficulty-level topic discovery.