18th AIAI 2022, 17 - 20 June 2022, Greece

Client Segmentation of Mobile Payment Parking Data using Machine Learning

Ilze Andersone, Agris Nikitenko, Valdis Bergs, Uldis Jansons


  This paper addresses the analysis of mobile payment parking data for client segmentation. The transaction data transformation into client-specific attributes is performed from the company data set to achieve the goal. Two clustering algorithms – K-Means and DBScan – are compared for multiple data subsets. For the clustering result interpretation, decision tree representation is used. As a result, the most appropriate combination of the clustering algorithm, its parameters and attribute combination is determined.  

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