Abstract
This paper built two modelsbased on the existing data of a mobile communication service provider. In the modern life, mobile phone has already become a necessity for us to take at any time. The position change of the mobile phone holder represents the cellular phone user’s move. A lot of promotion and other business activities are related to user’s position, and many business activities need to know the customers’ long-term move regulation. Therefore, the research of the cellular holder’s move principle is worthy now. The cellular phone customer move analysis of the paper is an analytical system based on the customer position. We conducted analysis for single time of the cellular phone customer ordering of position. We carried on analysis of several time positions and the relation of these positions. The mobile regulation of customer is analyzed by analyzing the relation of these positions. Different business activity can carry on promotion to the customer based on different regulation. According to the detection of the customer mobile regulation, the enterprise can discover new business application, and make more effectively business activities.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Page, T.: A Classification of Data Mining Techniques, First Quarter 2005 SME Technical Papers (2005)
Kiang, M.Y., Fisher, D.M., Fisher, S.A., Chi, R.T.: Understand Corporate Rationales for Engaging in Reverse Stock Splits - A Data Mining Application. In: The 38th Annual Hawaii International Conference on System Sciences (HICSS 2005) (2005)
Yaik, O.B., Yong, C.H., Haron, F.: Time series prediction using adaptive association rules, Information Theory. In: ISIT 2004. Proceedings. International Symposium (2005)
Kamrani, A., Rong, W., Gonzalez, R.: A genetic algorithm methodology for data mining and intelligent knowledge acquisition. Computers and Industrial Engineering 40(4), 361–377 (2001)
Fayyad, U., Stolorz, P.: Data mining and KDD: Promise and challenges. Future Generation Computer Systems 13(2-3), 99–115 (1997)
Hollmen, J., Tresp, V.: Call-based Fraud Detection in Mobile Communication Networks using a Hierarchical Regime-Switching Model
Rosset, S., Murad, U., Neumann, E., Idan, Y., Pinkas, G.: Discovery of Fraud Rules for Telecommunications-Challenges and Solutions
Hui, S.C., Jha, G.: Data mining for customer service support. Information & Management (38), 1–13 (2000)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2008 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Zhang, L., Li, J., Nie, G., Fu, H. (2008). The Knowledge Discovery Research on User’s Mobility of Communication Service Provider. In: Ishikawa, Y., et al. Advanced Web and Network Technologies, and Applications. APWeb 2008. Lecture Notes in Computer Science, vol 4977. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-89376-9_18
Download citation
DOI: https://doi.org/10.1007/978-3-540-89376-9_18
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-89375-2
Online ISBN: 978-3-540-89376-9
eBook Packages: Computer ScienceComputer Science (R0)