Do User (Browse and Click) Sessions Relate to Their Questions in a Domain-Specific Collection?
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We seek to improve information retrieval in a domain-specific collection by clustering user sessions as recorded in a click log and then classifying later user sessions in real-time. As a preliminary step, we explore the main assumption of this approach: whether user sessions in such a site relate to the question that they are answering. The contribution of this paper is the evaluation of the suitability of common machine learning measurements (measuring the distance between two sessions) to distinguish sessions of users searching for the answer to same or different questions. We found that sessions for people answering the same question are significantly different than those answering different questions, but results are dependent on the distance measure used. We explain why some distance metrics performed better than others.
KeywordsDistance Measure User Session Distance Score Average Pairwise Distance Cosine Vector
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