Abstract
Data mining applied to social media is gaining popularity. It is worth noticing that most e-commerce services also cause the formation of small communities not only services oriented toward socializing people. The results of their analysis are easier to implement. Besides, we can expect a better perception of the business by its own users, therefore the analysis of their behavior is justified. In the paper we introduce an algorithm which identifies particular customers among not logged or not registered users of a given e-commerce service. The identification of a customer is based on data that was given so as to accomplish selling procedure. Customers rarely use exactly the same identification data each time. In consequence, it is possible to check if customers create a group of unrelated individuals or if there are symptoms of social behavior.
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Gorawski, M., Chrószcz, A., Gorawska, A. (2013). Customer Unification in E-Commerce. In: Yin, H., et al. Intelligent Data Engineering and Automated Learning – IDEAL 2013. IDEAL 2013. Lecture Notes in Computer Science, vol 8206. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-41278-3_18
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DOI: https://doi.org/10.1007/978-3-642-41278-3_18
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