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In information retrieval, unbiased learning to rank refers to training ranking models from biased click logs by reweighting clicks with inverse propensity of examination so the learned objective is unbiased. This meaning comes from Joachims (2017) in Proceedings of the Tenth ACM International Conference on Web Search and Data Mining.[1]
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