Analysing Clustering Algorithms Performance in CRM Systems

Indrit Enesi, Ledion Liço, Aleksander Biberaj, Desar Shahu

Abstract

Customer Relationship Management technology plays an important role in business performance. The main problem is the extraction of valuable and accurate information from large customers’ transactional data sets. In data mining, clustering techniques group customers based on their transaction’s details. Grouping is a quantifiable way to analyse the customers’ data and distinguish customers based on their purchases. Number of clusters plays an important role in business intelligence. It is an important parameter for business analysts. In this paper the performance of K-means and K-medoids algorithm will be analysed based on the impact of the number of clusters, number of dimensions and distance function. The Elbow method combined with K-means algorithm will be implemented to find the optimal number of clusters for a real data set from retail stores. Results show that the proposed algorithm is very effective when customers need to be grouped based on numerical and nominal attributes.

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Paper Citation


in Harvard Style

Enesi I., Liço L., Biberaj A. and Shahu D. (2021). Analysing Clustering Algorithms Performance in CRM Systems. In Proceedings of the 23rd International Conference on Enterprise Information Systems - Volume 1: ICEIS, ISBN 978-989-758-509-8, pages 803-809. DOI: 10.5220/0010511008030809


in Bibtex Style

@conference{iceis21,
author={Indrit Enesi and Ledion Liço and Aleksander Biberaj and Desar Shahu},
title={Analysing Clustering Algorithms Performance in CRM Systems},
booktitle={Proceedings of the 23rd International Conference on Enterprise Information Systems - Volume 1: ICEIS,},
year={2021},
pages={803-809},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010511008030809},
isbn={978-989-758-509-8},
}


in EndNote Style

TY - CONF

JO - Proceedings of the 23rd International Conference on Enterprise Information Systems - Volume 1: ICEIS,
TI - Analysing Clustering Algorithms Performance in CRM Systems
SN - 978-989-758-509-8
AU - Enesi I.
AU - Liço L.
AU - Biberaj A.
AU - Shahu D.
PY - 2021
SP - 803
EP - 809
DO - 10.5220/0010511008030809