Relevance Feedback from Eye Movements for Proactive Information Retrieval

We study whether it is possible to infer from eye movements measured during reading what is relevant for the user in an information retrieval task. Inference is made using hidden Markov and discriminative hidden Markov models. The result of this feasibility study is that prediction of relevance is possible to a certain extent, and models benefit from taking into account the time series nature of the data.

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