Multimedia mining: towards the construction of a methodology and a non-structured date analytics tool
DOI:
https://doi.org/10.22395/rium.v16n31a6Keywords:
data mining, multimedia mining, data mining methodologies, data mining platformsAbstract
This research addresses the development of multimedia mining projects by applying analytical techniques to texts, images, audio, and video. In order to develop these projects, a methodology to develop multimedia mining projects (Multimedia Analytical Methodology-MAM) is proposed. Likewise, the construction of a software tool (known as Multimedia Analytical Platform-PAM) which allows the analysis of multimedia mining is introduced. Methodology and platform are evaluated with two study cases on prediction of mammography abnormalities and analysis of medical imaging similarity. Results obtained allowed validating the steps proposed in the MAM methodology and using the PAM platform to extract the characteristics of medical images, to apply data mining techniques, and to satisfactorily evaluate the results obtained.Downloads
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[2] E. A. Oviedo, A. I. Oviedo y G. L. Vélez, «MinerÃa de datos: aportes y tendencias en el servicio de salud de ciudades inteligentes», Revista Politécnica, vol. 11, n.º 20, pp. 111-120, 2015.
[3] J. Moine, «MetodologÃas para el descubrimiento de conocimiento en bases de datos: un estudio comparativo. Tesis de MaestrÃa» Universidad Nacional de la Plata, Argentina, 2013.
[4] A. Azevedo y L. Rojão, «KDD, SEMMA and CRISP-DM: a parallel overview», IADS-DM, pp. 182-185, 2008.
[5] O. Maimon y L. Rokach, Data mining and knowledge discovery handbook, New Rork: Springer, 2005.
[6] D. Pyle, Business modeling and data mining, Morgan Kaufmann, 2003.
[7] P. Santana, R. Costaguta y D. Missio, «Aplicación de algoritmos de clasificación de minerÃa de textos para el reconocimiento de habilidades de e-tutores colaborativos», Revista Iberoamericana de Inteligencia Artificial, pp. 57-67, 2014.
[8] M. Tapia, O. Ruiz y C. Chirinos, «Modelo de clasificación de opiniones subjetivas en redes sociales», IngenierÃa: Ciencia, TecnologÃa e Innovación, 2014.
[9] M. Hall, E. Frank, G. Holmes, B. Pfahringer, P. Reutemann y I. H. Witten, «The WEKA Data Mining Software: An Update», SIGKDD Explorations, pp. 10-18, 2009.
[10] M. Hofmann y K. Ralf, RapidMiner: Data Mining Use Cases and Business Analytics Applications, CRC Press, 2013.
[11] L. Torgo, Data mining with R: learning with case studies, Chapman & Hall / CRC., 2010.
[12] B. Devi, K. Rao, S. Setty y M. Rao, «Disaster Prediction System Using IBM SPSS Data Mining Tool», International Journal of Engineering Trends and Technology (IJETT), pp. 3352-3357, 2013.
[13] G. Fernandez, Data mining using SAS applications, CRC Press, 2010.
[14] A. I. Oviedo, J. Perea-Ortega, O. Ortega y E. Sanchis, «Video clustering based on the collaboration of multimedia clusterers,» de CLEI 2012 XXXVIII Conferencia Latinoamericana en Informática, MedellÃn, 2012.
[15] S. Suganthira, P. Thamilselvan, J. G. R. Sathiaseelan y M. Lakshmiprabha, «A Technical Study on Biomedical image Classification using Mining Algorithms,» de National Conference on Recent Advancements in Software Development (NCRASD-2015), Karaikudi, 2015.
[16] J. Suckling, J. Parker, D. R. Dance, S. Astley, I. Hutt, C. Boggis y J. Savage, «The mammographic image analysis society digital mammogram database,» In Exerpta Medica. International Congress Series, pp. 375-378, 1994.
[17] D. A. Wainwright, I. V. Balyasnikova, A. L. Chang, A. U. Ahmed, K. S. Moon, B. Auffinger y M. S. Lesniak, «IDO Expression in Brain Tumors Increases the Recruitment of Regulatory T Cells and Negatively Impacts Survival,» Clinical cancer research, vol. 18, n.º 22, pp. 6110-6121, 2012.
[18] J. Shiraishi, H. Abe, R. Engelmann y K. Doi, «Effect of high sensitivity in a computerized scheme for detecting extremely subtle solitary pulmonary nodules in chest radiographs: observer performance study», Academic radiology, vol. 10, n.º 11, pp. 1302-1311, 2003.
[19] J. Mena, Data mining your website, Digital Press, 1999.
[20] D. Corrales, A. Ledesma, A. Peña, J. Hoyos, A. Figueroa y J. Corrales, “A new dataset for coffee rust detection in Colombian crops base on classifiers,†Revista S&T, pp. 9-23, 2014.
[21] J. Riquelme, R. Ruiz y K. Gilbert, “MinerÃa de datos: Conceptos y tendencias,†vol. 10, nº 29, pp. 11-18, 2006.
[22] D. Torres, “Diseño y aplicación de una metodologÃa para análisis de noticias policiales utilizando minerÃa de textos,†Universidad de Chile, 2013.
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Published
2018-02-26
How to Cite
Oviedo Carrascal, E. A., Oviedo Carrascal, A. I., & Velez Saldarriaga, G. L. (2018). Multimedia mining: towards the construction of a methodology and a non-structured date analytics tool. Revista IngenierÃas Universidad De MedellÃn, 16(31), 125–142. https://doi.org/10.22395/rium.v16n31a6
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