Yann Vigile Hoareau

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Semantic spaces, such as the Latent Semantic Analysis (LSA), Hyperspace Analog to Language (HAL) or Random Indexing (RI), offer convenient methods to represent semantic relations between words and concepts, abstracted from a distribution of documents. The distribution of documents determines the local co-occurrence pattern between words all over the corpus(More)
Murat Ahat 1 Coralie Petermann 1, 2 Yann Vigile Hoareau 3 Soufian Ben Amor 1 Marc Bui 2 (1) Prism, Université de Versailles Saint-Quentin-en-Yvelines, 35 avenue des Etats-Unis, F-78035 Versailles. (2) LaISC, Ecole Pratique des Hautes Etudes, 41 rue Gay-Lussac, F-75005 Paris. (3) CHArt, 41 rue Gay-Lussac, F-75005 Paris. murat.ahat@prism.uvsq.fr,(More)
This paper proposes a model of text categorization named Alida, which combines a model of categorization inspired of the classical cognitive models of categorization of Nosofsky, with a semantic space model as system of semantic knowledge representation. The model addresses large-scale text categorization applications in opinion mining in different domains(More)
A model of episodic memory is derived to propose algorithms of text categorization with semantic space models. Performances of two algorithms named Target vector and Sub-target vector are contrasted using textual material of the text-mining context ‘DEFT09’. The experience reported here have been realized on the english corpus which is composed of articles(More)
A model of episodic memory is derived to propose algorithms of text categorization with semantic space models. Performances of two algorithms are contrasted using textual material of the text-mining context ‘DEFT09’. Results confirm that the episodic memory metaphor provides a convenient framework to propose efficient algorithm for text(More)
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