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Tsallis Mutual Information for Document Classification

Mutual information is one of the mostly used measures for evaluating image similarity. In this paper, we investigate the application of three different Tsallis-based generalizations of mutual information to analyze the similarity between scanned documents. These three generalizations derive from the Kullback–Leibler distance, the difference between entropy and conditional entropy, and the Jensen–Tsallis divergence, respectively. In addition, the ratio between these measures and the Tsallis joint entropy is analyzed. The performance of all these measures is studied for different entropic indexes in the context of document classification and registration

This work has been funded in part with Grant Numbers TIN2010-21089-C03-01 from the Spanish Government and 2009-SGR-643 from the Catalan Government.

MDPI (Multidisciplinary Digital Publishing Institute)

Director: Ministerio de Ciencia e Innovación (Espanya)
Generalitat de Catalunya. Agència de Gestió d’Ajuts Universitaris i de Recerca
Autor: Vila Duran, Marius
Bardera i Reig, Antoni
Feixas Feixas, Miquel
Sbert, Mateu
Resum: Mutual information is one of the mostly used measures for evaluating image similarity. In this paper, we investigate the application of three different Tsallis-based generalizations of mutual information to analyze the similarity between scanned documents. These three generalizations derive from the Kullback–Leibler distance, the difference between entropy and conditional entropy, and the Jensen–Tsallis divergence, respectively. In addition, the ratio between these measures and the Tsallis joint entropy is analyzed. The performance of all these measures is studied for different entropic indexes in the context of document classification and registration
This work has been funded in part with Grant Numbers TIN2010-21089-C03-01 from the Spanish Government and 2009-SGR-643 from the Catalan Government.
Accés al document: http://hdl.handle.net/2072/296040
Llenguatge: eng
Editor: MDPI (Multidisciplinary Digital Publishing Institute)
Drets: Attribution 3.0 Spain
URI Drets: http://creativecommons.org/licenses/by/3.0/es/
Matèria: Informació, Teoria de la
Information theory
Classificació
Classification
Títol: Tsallis Mutual Information for Document Classification
Tipus: info:eu-repo/semantics/article
Repositori: Recercat

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