We explore the use of eye movements as a source of implicit relevance feedback information. We construct a controlled information retrieval experiment where the relevance of each text is known, and test usefulness of implicit relevance feedback with it. If perceived relevance of a text can be predicted from eye movements, eye movement signal must contain information on the relevance. The result is that relevance can be predicted to a considerable extent with discriminative hidden Markov models, and clearly better than randomly already with simple linear models of time-averaged data.

This work was supported by the Academy of Finland, decision no. 79017, and by the IST Programme of the European Community, under the PASCAL Network of Excellence, IST-2002-506778.