Discovery of Customer Communities – Evaluation Aspects

Jerzy Korczak , Maciej Pondel , Wiktor Sroka


In the paper, a new multi-level hybrid method of community detection combining a density-based clustering with a label propagation method is evaluated and compared with the k-means benchmark and DBSCAN (Density-based spatial clustering of applications with noise). In spite of the sophisticated visualization methods, managers still usually find clustering results too difficult to evaluate and interpret. The article presents a set of key assessment measures that could be used to evaluate internal and external qualities of discovered clusters. The approach is validated on real life marketing database using advanced analytics platform, Upsaily.
Author Jerzy Korczak (MISaF / IBI / DIT) - [International University of Logistics and Transport in Wroclaw (MWSLiT)]
Jerzy Korczak,,
- Department of Information Technologies
- Międzynarodowa Wyższa Szkoła Logistyki i Transportu we Wrocławiu
, Maciej Pondel (BM / DBIiM)
Maciej Pondel,,
- Department of Business Intelligence in Management
, Wiktor Sroka (WUEB)
Wiktor Sroka,,
- Wroclaw University of Economics and Business
Publication size in sheets0.7
Book Ziemba Ewa (eds.): Information Technology for Management: Current Research and Future Directions, Lecture Notes in Business Information Processing, vol. 380, 2020, Springer, ISBN 9783030433529, [9783030433536], 264 p., DOI:10.1007/978-3-030-43353-6
Ziemba_E_Information_Technology.pdf / No licence information (file archived - login or check accessibility on faculty)
Keywords in EnglishClustering · Customer communities, Customer segmentation, Cluster evaluation, Marketing
Languageen angielski
Korczak_J_Pondel_M_Sroka_W_Discovery_of_Customer_Communities.pdf 2,02 MB
Score (nominal)20
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