Can eyes reveal interest? Implicit queries from gaze patterns

被引:0
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作者
Antti Ajanki
David R. Hardoon
Samuel Kaski
Kai Puolamäki
John Shawe-Taylor
机构
[1] Helsinki University of Technology (TKK),Department of Information and Computer Science, Helsinki Institute for Information Technology
[2] University College London,Department of Computer Science
关键词
Eye movements; Implicit relevance feedback; Information retrieval; Machine learning; Support vector machines;
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中图分类号
学科分类号
摘要
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 information 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.
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页码:307 / 339
页数:32
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