document: Automatically generating labels based on unified click model Ground truth labels are one of the most important parts in many test collections for information retrieval . Each label , depicting the relevance between a query-document pair , is usually judged by a human , and this process is time-consuming and labor-intensive . Automatically Generating labels from click-through data has attracted increasing attention . In this paper , we propose a Unified Click Model to predict the multi-level labels , which aims at comprehensively considering the advantages of the Position Models and Cascade Models . Experiments show that the proposed click model outperforms the existing click models in predicting the multi-level labels , and could replace the labels judged by humans for test collections .
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