Title :
Linguistic Evaluation in the Classification in Portuguese Texts
Author :
Camargo, Yuri ; Mello, Laila ; Leão, Jorge L S
Author_Institution :
GTA- Grupo de Teleinformatica e Automacao - COPPE/UFRJ, Rio de Janeiro
Abstract :
This paper evaluates the performance of support vector machines, Naive Bayes, and neural networks as classifiers for the categorization of Portuguese texts. We present several experiments with two different corpora with different feature selection strategies. We consider the use of linguistic information in the definition of grammatical groups. A comparison of classifiers is presented and the error margins show excellent results when using a specific feature selection in association with the right classifier.
Keywords :
Bayes methods; natural language processing; neural nets; pattern classification; support vector machines; text analysis; Naive Bayes; Portuguese text categorization; Portuguese texts; feature selection strategies; linguistic classification; linguistic evaluation; linguistic information; neural networks; support vector machines; Data mining; Information analysis; Intelligent networks; Intelligent systems; Machine intelligence; Neural networks; Nominations and elections; Support vector machine classification; Support vector machines; Text categorization;
Conference_Titel :
Intelligent Systems Design and Applications, 2007. ISDA 2007. Seventh International Conference on
Conference_Location :
Rio de Janeiro
Print_ISBN :
978-0-7695-2976-9
DOI :
10.1109/ISDA.2007.154