Journal of Information Systems Engineering and Management

Products Recommendation for Mobile Devices
Ruyther Parente da Costa 1 * , Caíque de Paula Pereira 1, Edna Dias Canedo 1
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1 Universidade de Brasília (UnB), BRAZIL
* Corresponding Author
Research Article

Journal of Information Systems Engineering and Management, 2017 - Volume 2 Issue 3, Article No: 16
https://doi.org/10.20897/jisem.201716

Published Online: 02 Aug 2017

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How to cite this article
APA 6th edition
In-text citation: (da Costa et al., 2017)
Reference: da Costa, R. P., Pereira, C. D. P., & Canedo, E. D. (2017). Products Recommendation for Mobile Devices. Journal of Information Systems Engineering and Management, 2(3), 16. https://doi.org/10.20897/jisem.201716
Vancouver
In-text citation: (1), (2), (3), etc.
Reference: da Costa RP, Pereira CDP, Canedo ED. Products Recommendation for Mobile Devices. J INFORM SYSTEMS ENG. 2017;2(3):16. https://doi.org/10.20897/jisem.201716
AMA 10th edition
In-text citation: (1), (2), (3), etc.
Reference: da Costa RP, Pereira CDP, Canedo ED. Products Recommendation for Mobile Devices. J INFORM SYSTEMS ENG. 2017;2(3), 16. https://doi.org/10.20897/jisem.201716
Chicago
In-text citation: (da Costa et al., 2017)
Reference: da Costa, Ruyther Parente, Caíque de Paula Pereira, and Edna Dias Canedo. "Products Recommendation for Mobile Devices". Journal of Information Systems Engineering and Management 2017 2 no. 3 (2017): 16. https://doi.org/10.20897/jisem.201716
Harvard
In-text citation: (da Costa et al., 2017)
Reference: da Costa, R. P., Pereira, C. D. P., and Canedo, E. D. (2017). Products Recommendation for Mobile Devices. Journal of Information Systems Engineering and Management, 2(3), 16. https://doi.org/10.20897/jisem.201716
MLA
In-text citation: (da Costa et al., 2017)
Reference: da Costa, Ruyther Parente et al. "Products Recommendation for Mobile Devices". Journal of Information Systems Engineering and Management, vol. 2, no. 3, 2017, 16. https://doi.org/10.20897/jisem.201716
ABSTRACT
The mobile application market and e-commerce sales have grown steadily, along with the growth of studies and product recommendation solutions implemented in e-commerce systems. In this context, this paper proposes a recommendation algorithm for mobile devices based on the COREL (CustOmer purchase pREdiction modeL) framework. The proposed recommendation algorithm is a customization of the COREL framework, based on the complexity of the implementation associated with iOS mobile applications. Therefore, this work aims to customize a gift recommendation algorithm in the context of mobile devices using as main input the user preferences for the gifts recommendation in the Giftr application.
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LICENSE
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.