It is generally assumed in the traditional formulation of supervised learning that only the outputs data are uncertain. However, this assumption might be too strong for some learni...
Patrick Dallaire, Camille Besse, Brahim Chaib-draa
Abstract. In text classification (TC) and other tasks involving supervised learning, labelled data may be scarce or expensive to obtain; strategies are thus needed for maximizing t...
The GRASIM (Graph-Aided Similarity calculation) algorithm is designed to solve the problem of ontology-based data matching. We subdivide the matching problem into the ones of restr...
In the ITEA2 Do-It-Yourself Smart Experiences project (DIY-SE), we are required to design an ontology-based ambient computing environment to support users to DIY their personalized...
In this paper, we propose a vector quantization (VQ) -based information hiding scheme that cluster the VQ codeowrds according the codewords' relation on Voronoi Diagram (VD). ...