In this paper we present a novel approach for labeling clusters of multimedia content that leverages supervised classification techniques in conjunction with unsupervised cluster...
Targeting the same objective of alleviating the manual work as automatic annotation, in this paper, we propose a novel framework with minimal human effort to manually annotate a l...
A huge amount of data and metadata emerges from Web 2.0 applications which have transformed the Web to a mass social interaction and collaboration medium. Collaborative Tagging Sy...
Eirini Giannakidou, Ioannis Kompatsiaris, Athena V...
Robust semantic labeling of image regions is a basic problem in representing and retrieving image/video content. We propose an SVM-MRF framework to model features and their spatia...
The purpose of text clustering in information retrieval is to discover groups of semantically related documents. Accurate and comprehensible cluster descriptions (labels) let the ...