Explainable Agreement through Simulation for Tasks with Subjective Labels

arXiv: Information Retrieval, Volume abs/1806.05004, 2018.

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The field of information retrieval often works with limited and noisy data in an attempt to classify documents into subjective categories, e.g., relevance, sentiment and controversy. We typically quantify a notion of agreement to understand the difficulty of the labeling task, but when we present final results, we do so using measures tha...More



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