This paper proposes an approach of extracting simple and effective features that enhances multilingual document ranking (MLDR). There is limited prior research on capturing the co...
In this paper we present an evaluation resource for geographic information retrieval developed within the Cross Language Evaluation Forum (CLEF). The GeoCLEF track is dedicated to...
Thomas Mandl, Fredric C. Gey, Giorgio Maria Di Nun...
This paper reports on the participation of ITC-irst in the Cross Language Evaluation Forum 2003; in particular, in the monolingual, bilingual, small multilingual, and spoken docum...
In one form or another language translation is a necessary part of cross-lingual information retrieval systems. Often times this is accomplished using machine translation systems....
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...