Big Data Decision Making Based on Predictive Data Analysis Using DEVS Simulations

Abstract : Methods of processing and analyzing traditional data does not answer to the emergence of Big Data stemming from social networks and mobile applications. One of the best ways to bring the perspective of the customers to business decisions is by using data analysis to allow a company to deal with the customer experience for improved management and better profits. The work in progress presented in this paper concerns the development of an approach integrating discrete-event Modeling and Simulation and statistical learning methods in order to perform both customer understanding through data classification and predictive modeling through data prediction. This work involves the integration of statistical learning algorithms in the DEVS formalism.
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Communication dans un congrès
3rd ACM SIGSIM Conference on Principles of Advanced Discrete Simulation, Jun 2015, London, United Kingdom. pp.257-258, 〈10.1145/2769458.2769491〉
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https://hal.archives-ouvertes.fr/hal-01245473
Contributeur : Laurent Capocchi <>
Soumis le : jeudi 17 décembre 2015 - 12:15:10
Dernière modification le : lundi 21 mars 2016 - 17:34:01

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Natacha Ellul, Laurent Capocchi, Jean François Santucci. Big Data Decision Making Based on Predictive Data Analysis Using DEVS Simulations. 3rd ACM SIGSIM Conference on Principles of Advanced Discrete Simulation, Jun 2015, London, United Kingdom. pp.257-258, 〈10.1145/2769458.2769491〉. 〈hal-01245473〉

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