We study a new research problem, where an implicit information retrieval query is inferred from eye movements measured when the user is reading, and used to retrieve new documents. In the training phase, the user's interest is known, and we learn a mapping from how the user looks at a term to the role of the term in the implicit query. Assuming the mapping is universal, that is, the same for all queries in a given domain, we can use it to construct queries even for new topics for which no learning data is available.

We constructed a controlled experimental setting to show that when the system has no prior infor- mation as to what the user is searching, the eye movements help significantly in the search. This is the case in a proactive search, for instance, where the system monitors the reading behaviour of the user in a new topic. In contrast, during a search or reading session where the set of inspected documents is biased towards being relevant, a stronger strategy is to search for content-wise similar documents than to use the eye movements.

This work was supported in part by the IST Programme of the European Community, under the PASCAL 2 Network of Excellence, and in part by TKK MIDE programme, project UI-ART. This publication only reflects the authors views. All rights are reserved because of other commitments.