This paper presents an effective fuzzy long-term semantic learning method for relevance feedback-based image retrieval. The proposed system uses a statistical correlationbased met...
This paper adopts the premise that the ‘semantic gap' is an incompletely surveyed feature in the landscape of visual image retrieval, and proposes a framework within which t...
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 ...
Motivated by the need to efficiently leverage user relevance feedback in content-based retrieval from image databases, we propose a fast, clustering-based indexing technique for e...
The structural features of XML components are an extra source of information that should be used in a contentoriented retrieval task on this type of documents. This paper explores...