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 ...
Abstract. It is well known that pseudo-relevance feedback (PRF) improves the retrieval performance of Information Retrieval (IR) systems in general. However, a recent study by Cao ...
Pseudo-relevance feedback assumes that most frequent terms in the pseudo-feedback documents are useful for the retrieval. In this study, we re-examine this assumption and show tha...
Guihong Cao, Jian-Yun Nie, Jianfeng Gao, Stephen R...
In this paper we investigate the effectiveness of a documentindependent technique for eliciting feedback from users about their information problems. We propose that such a techni...
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...