The classical probabilistic models attempt to capture the Ad hoc information retrieval problem within a rigorous probabilistic framework. It has long been recognized that the prim...
Pseudo-relevance feedback has proven to be an effective strategy for improving retrieval accuracy in all retrieval models. However the performance of existing pseudo feedback meth...
The University of Illinois at Urbana-Champaign (UIUC) participated in TREC 2007 Genomics Track. Our general goal of participation is to apply language modelbased approaches to the...
In this paper, we propose to model the blended search problem by assuming conditional dependencies among queries, VSEs and search results. The probability distributions of this mo...
Pseudo-relevance feedback (PRF) improves search quality by expanding the query using terms from high-ranking documents from an initial retrieval. Although PRF can often result in ...
Marc-Allen Cartright, James Allan, Victor Lavrenko...