Abstract
The Information Mining Engineering (IME) understands in processes, methodologies, tasks and techniques used to: organize, control and manage the task of finding knowledge patterns in information bases. A relevant task is selecting the data mining algorithms to use, which it is left to the expertise of the information mining engineer, developing it in a non-structured way. In this paper we propose an Information Mining Project Development Process Model (D-MoProPEI) which provides an integrated view in the selection of Information Mining Processes Based on Intelligent Systems (IMPbIS) within the Modeling Phase of the proposed Process Model through a Systematic Deriving Methodology.
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Acknowledgments
The research reported in this paper was partially funded by Project ME-SPU-PROMINF-UNLa-2015-2017 of the Argentinean Ministry of Education and Project UNLa-33A205 of the Secretary of Science and Technology of National University of Lanus (Argentina).
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Martins, S., Pesado, P., García-Martínez, R. (2016). Intelligent Systems in Modeling Phase of Information Mining Development Process. In: Fujita, H., Ali, M., Selamat, A., Sasaki, J., Kurematsu, M. (eds) Trends in Applied Knowledge-Based Systems and Data Science. IEA/AIE 2016. Lecture Notes in Computer Science(), vol 9799. Springer, Cham. https://doi.org/10.1007/978-3-319-42007-3_1
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