PASCAL - Pattern Analysis, Statistical Modelling and Computational Learning

Information Retrieval by Inferring Implicit Queries from Eye Movements
David Hardoon, John Shawe-Taylor, Antti Ajanki, Kai Puolamäki and Samuel Kaski
In: Eleventh International Conference on Artificial Intelligence and Statistic, March 21-24, 2007, San Juan, Puerto Rico.


We introduce a new search strategy, in which the information retrieval (IR) query is inferred from eye movements measured when the user is reading text during an IR task. In training phase, we know the users' interest. We learn a predictor which links eye movements related to a term to the role of that term in the query. Assuming this predictor is universal with respect to the users' interests, it can also be applied to infer the implicit query when we have no prior knowledge of the users' interests. The result of an empirical study is that it is possible to learn the implicit query from a small set of read documents, such that relevance predictions for a large set of unseen documents are ranked significantly better than by random guessing.

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EPrint Type:Conference or Workshop Item (Paper)
Project Keyword:Project Keyword UNSPECIFIED
Subjects:User Modelling for Computer Human Interaction
Information Retrieval & Textual Information Access
ID Code:2366
Deposited By:David Hardoon
Deposited On:22 November 2006