We demonstrate that regularization can improve feedback in a language modeling framework. Categories and Subject Descriptors: H.3.3 Information Search and Retrieval: Relevance Fee...
Relevance Feedback has proven very effective for improving retrieval accuracy. A difficult yet important problem in all relevance feedback methods is how to optimally balance the...
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...
Information retrieval algorithms leverage various collection statistics to improve performance. Because these statistics are often computed on a relatively small evaluation corpus...
In a previous work of ours Chinnakotla et al. (2010) we introduced a novel framework for Pseudo-Relevance Feedback (PRF) called MultiPRF. Given a query in one language called Sour...