Abstract
In data mining, the process of data obtained from users history databases is called Web usage mining. The main benefits lie in the improvement of the design of Web applications for the final user. This paper presents the application of subgroup discovery (SD) algorithms based on evolutionary fuzzy systems (EFSs) to the data obtained in an e-commerce Web site of extra virgin olive oil sale called http://www.orolivesur.com. For this purpose, a brief description of the SD process (objectives, properties, quality measures) and EFSs is presented. A discussion about the results obtained will also be included, especially focusing on the interests of the designer team of the Web site, providing some guidelines for improving several aspects such as usability and user satisfaction.
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Acknowledgments
This paper was supported by the Spanish Ministry of Education, Social Policy and Sports under project TIN-2008-06681-C06-02, FEDER Founds, by the Andalusian Research Plan under project TIC-3928, FEDER Founds, and by the University of Jaén Research Plan under proyect UJA2010/13/07 and Caja Rural sponsorship.
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Carmona, C., Jesus, M.d., García, S. (2014). Applying Subgroup Discovery Based on Evolutionary Fuzzy Systems for Web Usage Mining in E-Commerce: A Case Study on OrOliveSur.com. In: Sun, F., Li, T., Li, H. (eds) Foundations and Applications of Intelligent Systems. Advances in Intelligent Systems and Computing, vol 213. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-37829-4_50
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DOI: https://doi.org/10.1007/978-3-642-37829-4_50
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