We present a novel framework for integrating prior knowledge into discriminative classifiers. Our framework allows discriminative classifiers such as Support Vector Machines (SVMs...
In this paper we propose an integration of a selforganizing map and semantic networks from WordNet for a text classification task using the new Reuters news corpus. This neural mo...
Abstract. Activity inference based on object use has received considerable recent attention. Such inference requires statistical models that map activities to the objects used in p...
This paper describes our participation to the monolingual English GIRT task. The main objectives of our experiments were to evaluate the use of Mercure IRS (designed at IRIT/SIG) o...
This paper presents a vector space model approach, for representing documents and queries, using concepts instead of terms and WordNet as a light ontology. This way, information o...