In this paper, we propose a Bayesian learning approach to promoting diversity for information retrieval in biomedicine and a re-ranking model to improve retrieval performance in t...
To address the emerging needs of applications that require access to and retrieval of multimediaobjects, we are developing the Multimedia Analysis and Retrieval System (MARS) in o...
Michael Ortega, Yong Rui, Kaushik Chakrabarti, Sha...
Term-weighting schemes are vital to the performance of Information Retrieval models that use term frequency characteristics to determine the relevance of a document. The vector spa...
We propose a new probabilistic approach to information retrieval based upon the ideas and methods of statistical machine translation. The central ingredient in this approach is a ...
We report on the development of a new automatic feedback model to improve information retrieval in digital libraries. Our hypothesis is that some particular sentences, selected ba...
Patrick Ruch, Imad Tbahriti, Julien Gobeill, Alan ...