Tailoring click models to user goals

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Contextual Dueling Bandits (2015, methodology): “For the case that ε = O(ε′), and with ε′ as in Section 6, this algorithm gives a better bound by a factor of O(ln |Π|).”
Relative confidence sampling for efficient on-line ranker evaluation (2014, methodology): “Queries are sampled randomly and clicks are generated probabilistically by conditioning on these assessments using a user model that resembles the behavior of an actual user [11, 12].”
Click chain model in web search (2009, methodology): “search quality metrics, which correlate with user satisfaction [6].”
A probabilistic method for inferring preferences from clicks (2011, methodology): “The click model simulates user interactions according to the Dependent Click Model (DCM) [8, 9], an extension of the cascade model [6].”