Intelligent Method for Forming the Consumer Basket

• Published in: Information and Software Technologies Vol. 1665; pp. 221 - 231
• Main Authors: Lipianina-Honcharenko, Khrystyna, Wolff, Carsten, Chyzhovska, Zoriana, Sachenko, Anatoliy, Lendiuk, Taras, Grodskyi, Sergii
• Format: Book Chapter
• Language: English
• Published: Switzerland Springer International Publishing AG 2022; Springer International Publishing
• Series: Communications in Computer and Information Science
• Subjects: Clustering; Consumer basket; Dataset; k-means
• ISBN: 9783031163012; 303116301X
• ISSN: 1865-0929; 1865-0937
• DOI: 10.1007/978-3-031-16302-9_17

Authors developed an intelligent method of forming a consumer basket based on data from supermarket chains, which allows modifying the set of goods in the consumer basket and defining a living wage. The consumer basket is forming on a base of k-means clustering approach. The algorithmic structure of the proposed method is described. Experimental research is carried out using the Customer Personality Analysis dataset from the Kaggle platform. After data normalization and clustering, the clusters relative to the amount (USD) of purchased goods for 2 years were analyzed. As a result, the cluster (consumer basket) was selected which includes 27% of middle-aged customers of various ages and counts such goods as fish, meat, sweets, wine and equipment. The novelty of the paper is the automated and intelligent forming the set of goods in the consumer basket, which may promote survival during humanitarian and economic disasters, especially in times of economic crisis (war, pandemic).