ACM SIGIR 2008: Thirty-first Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, 20-24 July 2008, Singapore: Proceedings
ISBN
9781605581644
Event
31st Annual International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR 2008), Singapore
Pages (from-to)
817-818
Publisher
New York, NY: Association for Computing Machinery (ACM)
Organisations
Faculty of Science (FNWI) - Informatics Institute (IVI)
Abstract
We describe a method for applying parsimonious language models to re-estimate the term probabilities assigned by relevance models. We apply our method to six topic sets from test collections in five different genres. Our parsimonious relevance models (i) improve retrieval effectiveness in terms of MAP on all collections, (ii) significantly outperform their non-parsimonious counterparts on most measures, and (iii) have a precision enhancing effect, unlike other blind relevance feedback methods.
