The impact of big data market segmentation using data mining and clustering techniques

Author:

Yoseph Fahed12,Ahamed Hassain Malim Nurul Hashimah2,Heikkilä Markku1,Brezulianu Adrian3,Geman Oana4,Paskhal Rostam Nur Aqilah2

Affiliation:

1. Faculty of Social Sciences, Business and Economics, Åbo Akademi University, Turku, Finland

2. Department of School of Computer Sciences, Universiti Sains Malaysia, Penang, Malaysia

3. Faculty of Electronics, Telecommunications and Information Technology, Gheorghe Asachi Technical University, Iaşi, Romania

4. Department of Health and Human Development, Stefan cel Mare University, Suceava, Romania

Publisher

IOS Press

Subject

Artificial Intelligence,General Engineering,Statistics and Probability

Reference39 articles.

1. Patel A.B. , Birla M. and Nair U. , Addressing Big Data Problem Using Hadoop and Map Reduce, in 2012 Nirma University International Conference on Engineering (NUiCONE) (2012), pp. 1–5.

2. Chorianopoulos A. and Tsiptsis K. , Data Mining Techniques in CRM: Inside Customer Segmentation, no. 21. John Wiley & Sons., 2010.

3. David A. and Vassilvitskii S. , k-means++: The advantages of careful seeding, Proceedings of the eighteenth annual ACM-SIAM symposium on Discrete algorithms. Society for Industrial and Applied Mathematics, 2007.

4. Maximum Likelihood from Incomplete Data via the EM Algorithm;Dempster;J of the R Stat Soc Ser B,1977

5. Kak A. , Expectation-Maximization Algorithm for Clustering Multidimensional Numerical Data, Purdue University, 2017.

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