In information retrieval, relevance of documents with respect to queries is usually judged by humans, and used in evaluation and/or learning of ranking functions. Previous work ha...
Jingfang Xu, Chuanliang Chen, Gu Xu, Hang Li, Elbi...
Several algorithms have been proposed to learn to rank entities modeled as feature vectors, based on relevance feedback. However, these algorithms do not model network connections...
In this article, we present an object tracking system which allows interactive user feedback to improve the accuracy of the tracking process in real-time video. In addition, we des...
In this paper, we discuss the use of physiological data for quasi real-time adaptation in ITS. We present preliminary results where we analyze learners’ reactions while using a ...
Emmanuel G. Blanchard, Pierre Chalfoun, Claude Fra...
In this paper, we present a long term learning system for content based image retrieval over a network. Relevant feedback is used among different sessions to learn both the simila...