In order to minimize redundancy and optimize coverage of multiple user interests, search engines and recommender systems aim to diversify their set of results. To date, these dive...
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...
This paper describes QAST, a pilot track of CLEF 2007 aimed at evaluating the task of Question Answering in Speech Transcripts. The paper summarizes the evaluation framework, the ...
Jordi Turmo, Pere Comas, Christelle Ayache, Djamel...
In this paper, we propose a new approach to discover informative contents from a set of tabular documents (or Web pages) of a Web site. Our system, InfoDiscoverer, first partition...
Relevance feedback has been considered as a means of incorporating learning into information retrieval systems for quite sometime now. This paper discusses the research results of...