Modeling text with topics is currently a popular research area in both Machine Learning and Information Retrieval (IR). Most of this research has focused on automatic methods thou...
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...
LETOR is a benchmark collection for the research on learning to rank for information retrieval, released by Microsoft Research Asia. In this paper, we describe the details of the L...
Metonymic location names refer to other, related entities and possess a meaning different from the literal, geographic sense. Metonymic names are to be treated differently to im...
Some recent works have shown that the “perfect” selection of the best IR system per query could lead to a significant improvement on the retrieval performance. Motivated by thi...