Papers by Paul Felt

    1 papers
    Learning from Measurements in Crowdsourcing Models: Inferring Ground Truth from Diverse Annotation Types (C18-1)

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    Challenge: Annotated corpora are often assigned to internet workers whose judgments are reconciled by crowdsourcing models.
    Approach: They propose a framework for learning from rich prior knowledge to combine annotations with different structures.
    Outcome: The proposed model compares favorably with previous work and enables active sample selection to reduce annotation effort.

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