This paper presents the results of the State University of New York at Buffalo (UB) in the Mono-lingual and Multi-lingual tasks at CLEF 2004. For these tasks we used an approach ba...
Pseudo-relevance feedback (PRF) via query-expansion has been proven to be effective in many information retrieval (IR) tasks. In most existing work, the top-ranked documents from...
Language model (LM) adaptation is often achieved by combining a generic LM with a topic-specific model that is more relevant to the target document. Unlike previous work on unsup...
In our participation to the 2010 LogCLEF track we focused on the analysis of the European Library (TEL) logs and in particular we experimented with the identification of the natura...
This paper proposes a word sense language model based method for information retrieval. This method, differing from most of traditional ones, combines word senses defined in a thes...