Abstract
Customer’s segmentation is used as a marketing differentiation tool which allows organizations to understand their customers and build differentiated strategies. This research focuses on a database from the SMEs sector in Colombia, the CRISP-DM methodology was applied for the Data Mining process. The analysis was made based on the PFM model (Presence, Frequency, Monetary Value), and the following grouping algorithms were applied on this model: k-means, k-medoids, and Self-Organizing Maps (SOM). For validating the result of the grouping algorithms and selecting the one that provides the best quality groups, the cascade evaluation technique has been used applying a classification algorithm. Finally, the Apriori algorithm was used to find associations between products for each group of customers, so determining association according to loyalty.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Amelec, V.: Increased efficiency in a company of development of technological solutions in the areas commercial and of consultancy. Adv. Sci. Lett. 21(5), 1406–1408 (2015)
Varela, I.N., Cabrera, H.R., Lopez, C.G., Viloria, A., Gaitán, A.M., Henry, M.A.: Methodology for the reduction and integration of data in the performance measurement of industries cement plants. In: Tan, Y., Shi, Y., Tang, Q. (eds.) Data Mining and Big Data, DMBD 2018. LNCS, vol. 10943, pp. 33–42. Springer, Cham (2018). https://doi.org/10.1007/978-3-319-93803-5_4
Lis-Gutiérrez, J.P., Lis-Gutiérrez, M., Gaitán-Angulo, M., Balaguera, M.I., Viloria, A., Santander-Abril, J.E.: Use of the industrial property system for new creations in Colombia: a departmental analysis (2000–2016). In: Tan, Y., Shi, Y., Tang, Q. (eds.) Data Mining and Big Data, DMBD 2018. LNCS, vol. 10943, pp. 786–796. Springer, Cham (2018). https://doi.org/10.1007/978-3-319-93803-5_74
Anuradha, K., Kumar, K.A.: An e-commerce application for presuming missing items. Int. J. Comput. Trends Technol. 4, 2636–2640 (2013)
Larose, D.T., Larose, C.D.: Discovering Knowledge in Data (2014). https://doi.org/10.1002/9781118874059
Pickrahn, I., et al.: Contamination incidents in the pre-analytical phase of forensic DNA analysis in Austria—Statistics of 17 years. Forensic Sci. Int. Genet. 31, 12–18 (2017). https://doi.org/10.1016/j.fsigen.2017.07.012
de Barrios-Hernández, K.C., Contreras-Salinas, J.A., Olivero-Vega, E.: La Gestión por Procesos en las Pymes de Barranquilla: Factor Diferenciador de la Competitividad Organizacional. Información tecnológica 30(2), 103–114 (2019)
Prajapati, D.J., Garg, S., Chauhan, N.C.: Interesting association rule mining with consistent and inconsistent rule detection from big sales data in distributed environment. Future Comput. Inform. J. 2, 19–30 (2017). https://doi.org/10.1016/j.fcij.2017.04.003
Abdullah, M., Al-Hagery, H.: Classifiers’ accuracy based on breast cancer medical data and data mining techniques. Int. J. Adv. Biotechnol. Res. 7, 976–2612 (2016)
Khanali, H.: A survey on improved algorithms for mining association rules. Int. J. Comput. Appl. 165, 8887 (2017)
Ban, T., Eto, M., Guo, S., Inoue, D., Nakao, K., Huang, R.: A study on association rule mining of darknet big data. In: 2015 International Joint Conference on Neural Networks, pp. 1–7 (2015). https://doi.org/10.1109/IJCNN.2015.7280818
Vo, B., Le, B.: Fast algorithm for mining generalized association rules. Int. J. Database Theory Appl. 2, 1–12 (2009)
Al-Hagery, M.A.: Knowledge discovery in the data sets of hepatitis disease for diagnosis and prediction to support and serve community. Int. J. Comput. Electron. Res. 4, 118–125 (2015)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2019 Springer Nature Singapore Pte Ltd.
About this paper
Cite this paper
Silva, J. et al. (2019). Association Rule Mining for Customer Segmentation in the SMEs Sector Using the Apriori Algorithm. In: Singh, M., Gupta, P., Tyagi, V., Flusser, J., Ören, T., Kashyap, R. (eds) Advances in Computing and Data Sciences. ICACDS 2019. Communications in Computer and Information Science, vol 1046. Springer, Singapore. https://doi.org/10.1007/978-981-13-9942-8_46
Download citation
DOI: https://doi.org/10.1007/978-981-13-9942-8_46
Published:
Publisher Name: Springer, Singapore
Print ISBN: 978-981-13-9941-1
Online ISBN: 978-981-13-9942-8
eBook Packages: Computer ScienceComputer Science (R0)