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http://repositorio.ufla.br/jspui/handle/1/12289| Title: | Analysis of machine learning techniques to classify news for information management in coffee market |
| Other Titles: | Análise de técnicas de aprendizado de máquina para classificar notícias para gerencimento de informação no mercado de café |
| Keywords: | Gerenciamento de recursos de informação Café Sistema computacional Árvore de decisão Classificador Naive Bayes Máquinas de vetores de suporte Information resources management Coffee Computational system Decision tree Naïve Bayes classifier Support vector machines |
| Issue Date: | Jul-2015 |
| Publisher: | IEEE América Latina |
| Citation: | LIMA JÚNIOR, P. O.; CASTRO JÚNIOR, L. G. de; ZAMBALDE, A. L. Analysis of machine learning techniques to classify news for information management in coffee market. Revista do IEEE América Latina, [S. l.], v. 13, n. 7, p. 2285-2291, July 2015. Texto em português. |
| Abstract: | This paper presents an empirical study of machine learn techniques to text categorization. Specifically aim to classify news about coffee market according with categories from coffee supply chain. The objective is to measure the performance of three types of algorithms: Naïve Bayes based, Tree bases and Support Vector Machine (SVM). A database with news collected from web and labeled by human expert analysts is used in a learning phase. Then automatic classify news extracted from web following the same steps and terms as human according to their relevance for each learned category. The test in a real database shows a better performance by Naïve Bayes based Algorithms for this specific case. |
| URI: | http://www.ewh.ieee.org/reg/9/etrans/ieee/issues/vol13/vol13issue07July2015/36OliveiraLimaJunior.htm http://repositorio.ufla.br/jspui/handle/1/12289 |
| Appears in Collections: | DCC - Artigos publicados em periódicos |
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