Abstract
Many companies are now developing an online internet presence to sell or promote their products and services. The data generated by e-commerce sites is a valuable source of business knowledge but only if it is correctly analyzed. Data mining web server logs is now an important application area for business strategy. We describe an e-commerce system specifically developed for the purpose of demonstrating the advantages of data mining web server logs. We also provide details of system implementation which was developed in Java. The data generated by the server logs is used by a rule induction algorithm to build a profile of the users, the profile enables the web site to be personalized to each particular customer. The ability to rapidly respond and anticipate customer behavior is vital to stay ahead of the competition.
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McGarry, K., Martin, A., Addison, D. Data Mining and User Profiling for an E-Commerce System. In: K. Halgamuge, S., Wang, L. (eds) Classification and Clustering for Knowledge Discovery. Studies in Computational Intelligence, vol 4. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11011620_12
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DOI: https://doi.org/10.1007/11011620_12
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Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-26073-8
Online ISBN: 978-3-540-32404-1
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