Abstract
The objective of this paper is to set the strategic planning on upcoming products using partitional clustering algorithms. Extensive experiments have been conducted on the proposed algorithm to establish our claims. The experiments performed on synthetic and real datasets showed the effectiveness of our proposed algorithm.
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References
C.Y. Lin, J.L. Koh, A.L.P. Chen, Determining k-most demanding products with maximum expected number of total customers. IEEE Trans. Knowl. Data Eng. 25(8), 1732–1747 (2013)
N.G. Mankiw, Principle of Economics, 5th edn. (South Western College Publication, New York, 2008)
R. Kumar, P.S. Bishnu, V. Bhattacherjee, K-Means algorithm to identify k1-most demanding products, in PReMI 2017. LNCS vol. 10597 (2017), pp. 451–457
E. Brentari, L. Dancelli, M. Manisera, Clustering ranking data in market segmentation: a case study on the Italian McDonald’s customers’ preferences. J. Appl. Stat. 43(11), 1959–1976 (2016). https://doi.org/10.1080/02664763.2015.1125864
X. Chen, Y. Fang, M. Yang, F. Nie, Z. Zhao, J.Z. Huang, PurTreeClust: a clustering algorithm for customer segmentation from massive customer transaction data. IEEE Trans. Knowl. Data Eng. 30(3), 559–572 (2018)
S. Masood, M. Ali, F. Arshad, A.M. Qamar, A. Kamal, A. Rehman, Customer segmentation and analysis of a mobile telecommunication company of Pakistan using two phase clustering algorithm, in Eighth International Conference on Digital Information Management (ICDIM, 2014)
C.P. Ezenkwu, S. Ozuomba, C. Kalu, Application of K-Means algorithm for efficient customer segmentation: a strategy for targeted customer services. Int. J. Adv. Res. Artif. Intell. 4(10) (2015)
A. Ansari, A. Riasi, Customer clustering using a combination of fuzzy C-Means and genetic algorithms. Int. J. Bus. Manage. 11(7) (2016)
R.-S. Wu, P.-H. Choub, Customer segmentation of multiple category data in e-commerce using a soft-clustering approach. Electron. Commer. Res. Appl. 10(3), 331–341 (2011)
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Kumar, R., Bishnu, P.S. (2020). Target Marketing Using Feedback Mining. In: Sahana, S., Bhattacharjee, V. (eds) Advances in Computational Intelligence. Advances in Intelligent Systems and Computing, vol 988. Springer, Singapore. https://doi.org/10.1007/978-981-13-8222-2_8
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DOI: https://doi.org/10.1007/978-981-13-8222-2_8
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