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Understanding and modeling user behavior is critical to designing search systems: it allows us to drive batch evaluations, predict how users would respond to changes in systems or interfaces, and suggest ideas for improvement. In this work we present a comprehensive model of the interactions between a searcher and a search engine, and the decisions users make in these interactions. The model is designed to deal only with observable phenomena. Based on data from a user study, we are therefore able to make initial estimates of the probabilities associated with various decision points.
Thomas et al. (Thu,) studied this question.
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