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...
Users of image databases often prefer to retrieve relevant images by categories. Unfortunately, images are usually indexed by low-level features like color, texture and shape, whi...
In this paper we present a system which uses ontological resources and a gene name variation generation tool to expand concepts in the original query. The novelty of our approach ...
Nicola Stokes, Yi Li, Lawrence Cavedon, Eric Huang...
We evaluate three different relevance feedback (RF) algorithms, Rocchio, Robertson/Sparck-Jones (RSJ) and Bayesian, in the context of Web search. We use a target-testing experimen...
Vishwa Vinay, Kenneth R. Wood, Natasa Milic-Frayli...
Content-based image retrievalsystems use low-levelfeatures like color and texturefor image representation. Given these representationsasfeature vectors, similarity between images ...
Selim Aksoy, Robert M. Haralick, Faouzi Alaya Chei...