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. (2014). User Identity Unification in e-Commerce. In: Swiątek, J., Grzech, A., Swiątek, P., Tomczak, J. (eds) Advances in Systems Science. Advances in Intelligent Systems and Computing, vol 240. Springer, Cham. https://doi.org/10.1007/978-3-319-01857-7_16
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DOI: https://doi.org/10.1007/978-3-319-01857-7_16
Publisher Name: Springer, Cham
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