Multicriteria analysis for behavioral segmentation

• Autorzy: Granat J.
• Języki publikacji: EN

Abstrakty

EN

Behavioral segmentation is a process of finding the groups of clients with similar behavioral patterns. The basic tool for segmentation is a clustering algorithm. However, the clusters generated by the algorithm depend on the preprocessing steps as well as parameters of the algorithm. Therefore, there are many possibilities of dividing the clients into segments and it is a subjective process. In this paper we will focus on application on multicriteria analysis for selecting the best partition of clients into segments.

Słowa kluczowe

EN

segmentation; clustering; multicriteria analysis; telecommunications

• Wydawca: Instytut Łączności - Państwowy Instytut Badawczy
• Czasopismo: Journal of Telecommunications and Information Technology
• Rocznik: 2004
• Tom: nr 3
• Strony: 39--43
• Opis fizyczny: Bibliogr. 10 poz., il., tab.

Twórcy

autor

Granat J.

• National Institute of Telecommunications, Szachowa st 1, 04-894 Warsaw, Poland. Institute of Control and Computation Engineering, Warsaw University Technology, Nowowiejska st 15/19, 00-665 Warsaw, Poland,

Bibliografia

• [1] J.-L. Amat, „Using reporting and data mining techniques to improve knowledge of subscribers; applications to customer profling and fraud management", J. Telecommun. Inform. Technol., no. 3, pp. 11-16, 2002.
• [2] J. Granat, „Data mining and complex telecommunications problems modeling", J. Telecommun. Inform. Technol., no. 3, pp. 115-120, 2003.
• [3] J. Granat and M. Makowski, „Interactive specification and analysis of aspiration-based preferences", Eur. J. Oper. Res., vol. 122, no. 3, pp. 469-485, 2000.
• [4] J. He, A.-H. Tan, C.-L. Tan, and S.-Y. Sung, „On quantitative evaluation of clustering algorithms", in Clustering and Information Retrieval, W. Wu, H. Xiong, and S. Shekhar, Eds. Kluwer, 2003.
• [5] K. Mali, „Clustering and its validation in a symbolic framework", Patt. Recogn. Lett., vol. 24, pp. 2367-2376, 2003.
• [6] R. Mattison, Data Warehousing and Data Mining for Telecommunications. Boston, London: Artech House, 1997.
• [7] M. McDonald and I. Dunbar, „Market segmentation. How to do it, how to profit from it". Palgrave Publ., 1998.
• [8] E. Orłowska, „Dynamic information systems", in Annales Societatis Mathematicae Polonae, Series IV: Fundamenta Informaticae, vol. 5, no. 1, pp. 101-118, 1982.
• [9] M. Shawa, C. Subramaniama, G. Tana, and M. Welgeb, „Knowledge management and data mining for marketing", Decis. Supp. Syst., vol. 31, no. 1, pp. 127-137, 2001.
• [10] P. Verhoef, P. Spring, J. Hoekstra, and P. Leeang, „The commercial use of segmentation and predictive modeling techniques for database marketing in the Netherlands", Decis. Supp. Syst., vol. 34, pp. 471-481, 2002.