The goal of the Rutgers TREC-6 Interactive Track study was to compare the performance and usability of a system offering positive relevance feedback with one offering positive and...
Nicholas J. Belkin, Jose Perez Carballo, Colleen C...
This paper focuses on the retrieval of complex images based on their textural content. We use GMRF for texture discrimination and a region-growing algorithm for texture segmentati...
Eugenio Di Sciascio, Giacomo Piscitelli, Augusto C...
In this report we describe our model of dynamic hypertext and how the ClickIR system uses this model to assist users in interactive search. The system was used in both the ad hoc ...
Content-Based Image Retrieval (CBIR) has become one of the most active research areas in the past few years. Many visual feature representations have been explored and many system...
Relevance feedback is a powerful query modification technique in the field of content-based image retrieval. The key issue in relevance feedback is how to effectively utilize the ...
In this paper, we report our experiments on the HARD (High Accuracy Retrieval from Documents) Track in TREC 2003. We focus on active feedback, i.e., how to intelligently propose q...
This paper describes the experiments conducted in the ad-hoc retrieval task of the Genomic track at TREC 2004. Different query expansion techniques based on the addition of keywor...
: Content-based image retrieval (CBIR) is a research area dedicated to address the retrieve and search multimedia documents for digital libraries. Relevance feedback is a powerful ...
Personalisation in full text retrieval or full text filtering implies reweighting of the query terms based on some explicit or implicit feedback from the user. Relevance feedback i...
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...