Traditional adaptive filtering systems learn the user’s interests in a rather simple way – words from relevant documents are favored in the query model, while words from irre...
Today's Content-Based Image Retrieval (CBIR) techniques are based on the "k-nearest neighbors" (kNN) model. They retrieve images from a single neighborhood using lo...
In this paper we present an interactive, object-based video retrieval system which features a novel query formulation method that is used to iteratively refine an underlying model...
Sorin Sav, Hyowon Lee, Noel E. O'Connor, Alan F. S...
Closing the semantic gap in content based image retrieval (CBIR) basically requires the knowledge of the user's intention which is usually translated into a sequence of quest...
Relevance feedback (RF) is an interactive process which refines the retrievals by utilizing user’s feedback history. Most researchers strive to develop new RF techniques and ign...
Peng-Yeng Yin, Bir Bhanu, Kuang-Cheng Chang, Anlei...