Collective clustering of marketing data— recommendation system Upsaily

Maciej Pondel , Jerzy Korczak


Abstract—The article discusses the importance of the recom- mendation systems based on data mining mechanisms targeting the e-commerce industry. The article focuses on the use of clustering algorithms to conduct customer segmentation. Results of the operation of many clustering algorithms in segmentation inspired by the RFM method are presented, and the method of collective clustering using the positive effects of each algorithm is separately presented
Author Maciej Pondel (MISaF / IBI / DBIiM)
Maciej Pondel,,
- Department of Business Intelligence in Management
, Jerzy Korczak (MISaF / IBI / DIT) - [inna]
Jerzy Korczak,,
- Department of Information Technologies
- inna
Publication size in sheets0.5
Book Ganzha Maria, Maciaszek Leszek, Paprzycki Marcin (eds.): Proceedings of the 2018 Federated Conference on Computer Science and Information Systems, Annals of Computer Science and Information Systems, vol. 15, 2018, Polskie Towarzystwo Informatyczne, ISBN 9788394941956, [9788394941963, 9788394941970], 1089 p., DOI:10.15439/978-83-949419-5-6
Languageen angielski
Pondel_Korczak_Collective_clustering_of_marketing2018.pdf 1,18 MB
Score (nominal)15
Score sourceconferenceIndex
Publication indicators WoS Citations = 0
Citation count*4 (2020-08-07)
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* presented citation count is obtained through Internet information analysis and it is close to the number calculated by the Publish or Perish system.