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CIKM
2010
Springer

Predicting short-term interests using activity-based search context

8 years 7 months ago
Predicting short-term interests using activity-based search context
A query considered in isolation offers limited information about a searcher's intent. Query context that considers pre-query activity (e.g., previous queries and page visits), can provide richer information about search intentions. In this paper, we describe a study in which we developed and evaluated user interest models for the current query, its context (from pre-query session activity), and their combination, which we refer to as intent. Using large-scale logs, we evaluate how accurately each model predicts the user's short-term interests under various experimental conditions. In our study we: (i) determine the extent of opportunity for using context to model intent; (ii) compare the utility of different sources of behavioral evidence (queries, search result clicks, and Web page visits) for building predictive interest models, and; (iii) investigate optimally combining the query and its context by learning a model that predicts the context weight for each query. Our find...
Ryen W. White, Paul N. Bennett, Susan T. Dumais
Added 13 May 2011
Updated 13 May 2011
Type Journal
Year 2010
Where CIKM
Authors Ryen W. White, Paul N. Bennett, Susan T. Dumais
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