Promotion Assistance Tool for Mobile Phone Users

  • P. Intraprasert
  • N. Jatikul
  • C. Chantrapornchai
Part of the Communications in Computer and Information Science book series (CCIS, volume 124)


In this paper, we propose an application tool to help analyze the usage of a mobile phone for a typical user. From the past usage, the tool can analyze the promotion that is suitable for the user which may save the total expense. The application consists of both client and server side. On the server side, the information for each promotion package for a phone operator is stored as well as the usage database for each client. The client side is a user interface for both phone operators and users to enter their information. The analysis engine are based on KNN, ANN, decision tree and Naïve Bayes models. For comparison, it is shown that KNN and decision outperforms the others.


Mobile phone usage analysis Phone promotion package KNN ANN Decision tree Naïve Bayes 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Jirapaisarnkul, C.: Data mining for selling analysis, Master thesis, Sripatum University (2004)Google Scholar
  2. 2.
    Fayyad, U.M., Piatetsky-Shapiro, G., Smyth, P., Uthurusamy, R.: Advances in knowledge discovery and data mining. AAAI/MIT Press (1996)Google Scholar
  3. 3.
    Saenghamud, P., et al.: A Development of Information Technology System for Knowledge Management by Naive Bayesian incase in Restaurant and Bakery Business. In: Proceedings of the 1st NCTechED, pp. 14–21 (2008)Google Scholar
  4. 4.
    Pornpacharapong, V.: Risk Factors Affecting Money Saving Behavior of Thai People in Rural Area using Artificial Neural Networks. In: Proceedings of the 5th Operation Research Conference, pp. 284–289 (2008)Google Scholar
  5. 5.
  6. 6.
  7. 7.
  8. 8.

Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • P. Intraprasert
    • 1
  • N. Jatikul
    • 1
  • C. Chantrapornchai
    • 1
  1. 1.Department of Computing, Faculty of ScienceSilpakorn UniversityNakorn PathomThailand

Personalised recommendations