Modeling data mining applications for prediction of prepaid churn in telecommunication services;Modeliranje data mining aplikacija za detekciju churna prepaid korisnika telekomunikacijskih usluga

Automatika

Volumn 51, Issue 3, 2010, Pages 275-283

  Kraljevíc, Goran ^a   Gotovac, Sven ^b  

^a HT Mostar Kneza Branimira bb   (Croatia)

^b UNIVERSITY OF SPLIT   (Croatia)

Author keywords

Data Mining applications; Decision trees; Logistic regression; Neural networks; Prepaid churn model

Indexed keywords

EID: 78649902547     PISSN: 00051144     EISSN: None     Source Type: Journal    
DOI: 10.1080/00051144.2010.11828381     Document Type: Article

References (20)

1. Michael J. A. Berry, Gordon S. Linoff: "r;Data Mining Techniques: For Marketing, Sales and Customer Relationship Management";, Wiley Publishing, Indidana, 2004.
2. Ian H. Witten, Eibe Frank: "r;Data Mining: Practical Machine Learning Tools and Techniques";, Morgan Kaufmann Publishers, San Francisco, 2005.
3. Paolo Giudici, Silvia Figini: "r;Applied Data Mining for Business and Industry", John Wiley & Sons, 2009.
4. David L. Olson, Dursun Delen: "Advanced Data Mining Techniques", Springer, 2008.
5. L. A. Kurgan, P. Musilek: "A survey of Knowledge Discovery and Data Mining process models", The Knowledge Engineering Review, Vol.21, pp.1-24, 2006.
6. K. Cios, L.A. Kurgan: "Trends in Data Mining and knowledge discovery"- in N.Pal, L.Jain (eds): "r;Advanced Techniques in Knowledge Discovery and Data Mining";, Springer, pp. 1-26., 2005.
7. T. Li, D. Ruan: "r;An extended process model of knowledge discovery in databases", Journal of Enterprise Information Management, Volume 20, Number 2, pp. 169-177(9), 2007.
8. T. Reinartz: "r;Stages of the discovery process";- In W.Klosgen, J.Zytkow (eds): "r;Handbook of DataMining and Knowledge Discovery";, Oxford University Press, pp. 185-192., 2002.
9. P. González-Aranda, E. Menasalvas, S. Millán, C. Ruiz, J. Segovia: "Towards a Methodology for Data Mining Project Development: The Importance of Abstraction", Volume 118/2008, Springer, pp. 165-178., 2008.
10. M. Van Rooyen: "An evaluation of the utility of two Data Mining project methodologies"- In S.J.Simoff, G.Williams (eds): "r;Proceedings of the 3rd Australasian Data Mining Conference";, Cairns, Australia, pp. 85-94., 2004.
11. Wayne W. Eckerson: "Predictive Analytics - Extending the Value of Your Data Warehousing Investment", TDWI (The Data Warehousing Institute), 2007.
12. C. Shearer: "The CRISP-DM Model: The new blueprint for Data Mining", Journal of Data Warehousing, Volume 5, Number 4, Fall 2000, pp.13-22, 2000.
13. R. Mattison: ";The Telco Churn Management Handbook", XiT Press, Oakwood Hills, Illinois, 2005.
14. G. Kraljevíc, I. Krasíc, S. Gotovac: "Data Mining Techniques and Applications in Telecommunication Systems", MIPRO 2007., BIS - Business Intelligence Systems, pp. 257-261, 2007.
15. Marko Ferišak: "r;Intelligent Automata Models in Data Mining Processes for Telecommunication Service Forecasting";, PhD Thesis, FER, Zagreb, 2005.
16. S.M.H. Jansen: "Customer Segmentation and Customer Profiling for a Mobile Telecommunications Company Based on Usage Behavior", A Vodafone Case Study July, 2007.
17. E.W.T. Ngai, Li Xiu, D.C.K. Chau: "Application of Data Mining techniques in customer relationship management: A literature review and classification", Expert Systems with Applications: An International Journal, v.36 n.2, pp. 2592-2602, 2009.
18. A.T.Jahromi, M.Moeini, I.Akbari, A.Akbarzadeh: "A dualstep multi-algorithm approach for churn prediction in Prepaid telecommunications service providers", ICIM 2009, Sao Paulo, Brazil, Dec.2009.
19. CRISP-DM: Cross Industry Standard Process Model for Data Mining (http://www.crisp-dm.org), 2010.
20. WEKA (Open source, Data Mining software in Java), University of Waikato, New Zealand (http://www.cs.waikato.ac.nz/ml/weka), Weka 3.7.0., 2010.