Data Mining: Applications, tools, learning types and other subtopics

Authors

  • Deborah Ribeiro Carvalho Programa de Pós-Graduação em Tec. Aplicada à Saúde - PUC PR
    • Marcelo Rosano Dallagassa Unimed Paraná

      DOI:

      https://doi.org/10.5380/atoz.v3i2.41340

      Keywords:

      data mining, data mining tools, Data Mining use

      Abstract

      Experts in the field of data mining present concepts, features, limitations and possibilities of the data mining process, including the indication of tools available, links to artificial intelligence, and the implications of it's use in business intelligence.

      Author Biographies

      Deborah Ribeiro Carvalho, Programa de Pós-Graduação em Tec. Aplicada à Saúde - PUC PR

      Graduada em Processamento de Dados - UFPR, Mestre em Informática Aplicada - PUC PR, Doutora em Computação - UFRJ/COPPE, Doutora em Informática Aplicada - PUC PR. Professor e pesquisador no Programa de Pós-Graduação em Tecnologia Aplicada à Saúde - PUC/PR

      Marcelo Rosano Dallagassa, Unimed Paraná

      Bacharel em Engenharia Civil - UFPR, Mestre em Tecnologia em Saúde - PUC-PR. Analista de Negócios e Especialista - UNIMED PARANÁ

      References

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      Demsar, J., Zupan, B., Leban, G., & Curk, T. (2004). Orange: From experimental machine learning to interactive data mining. 8th European Conference on Principles and Practice of Knowledge Discovery in Databases, 537-539. doi: 10.1007/978-3-540-30116-5_58

      Fayyad, U. M., Piatetsky Shapiro, G., Smyth, P., & Uthurusamy, R. (1996). Advances in Knowledge Discovery and Data Mining. California, USA: AAAI, MIT.

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      Ingersoll, G. (2009). Introducing Apache Mahout Scalable, commercial-friendly machine learning for building intelligent applications. Retirado de http://www.ibm.com/developerworks/java/library/j-mahout/j-mahout-pdf.pdf

      Rakotomalala, R. (2005). TANAGRA: a free software for research and academic purposes. Proceedings of EGC RNTI-E-3, 2th, 697-702. Retirado de http://eric.univ-lyon2.fr/~ricco/tanagra/en/tanagra.html

      Seidman, C. (2001). Data mining with Microsoft SQL Server 2000 technical reference. Redmond: Microsoft.

      Tamayo, P., Berger, C., Campos, M., Yarmus, J., Milenova, B., Mozes, A., ... , & Myczkowski, J. (2005). Oracle data mining. In Maimon, O., & Rokach, L. (Eds.). Data Mining and Knowledge Discovery Handbook (1315-1329). New York: Springer. doi: 10.1007/0-387-25465-X_63

      Witten I. H., & Frank E. (2000). Machine learning algorithms in Java. Retirado de http://www.cs.waikato.ac.nz/ml/weka/

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      Published

      2014-12-31

      How to Cite

      Carvalho, D. R., & Dallagassa, M. R. (2014). Data Mining: Applications, tools, learning types and other subtopics. AtoZ: Novas práticas Em informação E Conhecimento, 3(2), 82–86. https://doi.org/10.5380/atoz.v3i2.41340

      Issue

      Vol. 3 No. 2 (2014): jul./dez.

      Section

      Interviews

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