Abstract
We develop a novel probabilistic approach to ad hoc retrieval that explicitly addresses the uncertainty about the information need underlying a given query. In doing so, we account for the special role of the corpus in the retrieval process. The derived retrieval method integrates multiple relevance models by using estimates of their faithfulness to the presumed information need. Empirical evaluation demonstrates the performance merits of the proposed approach.
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Soskin, N., Kurland, O., Domshlak, C. (2009). Navigating in the Dark: Modeling Uncertainty in Ad Hoc Retrieval Using Multiple Relevance Models. In: Azzopardi, L., et al. Advances in Information Retrieval Theory. ICTIR 2009. Lecture Notes in Computer Science, vol 5766. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-04417-5_8
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DOI: https://doi.org/10.1007/978-3-642-04417-5_8
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-04416-8
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