Semantic Scholar Open Access 2006 560 sitasi

Applying data mining to telecom churn management

S. Hung D. Yen Hsiu-Yu Wang

Lihat Sumber DOI

Abstrak

Abstract Taiwan deregulated its wireless telecommunication services in 1997. Fierce competition followed, and churn management becomes a major focus of mobile operators to retain subscribers via satisfying their needs under resource constraints. One of the challenges is churner prediction. Through empirical evaluation, this study compares various data mining techniques that can assign a ‘propensity-to-churn’ score periodically to each subscriber of a mobile operator. The results indicate that both decision tree and neural network techniques can deliver accurate churn prediction models by using customer demographics, billing information, contract/service status, call detail records, and service change log.

Topik & Kata Kunci

Computer Science

Penulis (3)

S. Hung

D. Yen

Hsiu-Yu Wang

Format Sitasi

APA MLA BibTeX

Hung, S., Yen, D., Wang, H. (2006). Applying data mining to telecom churn management. https://doi.org/10.1016/j.eswa.2005.09.080

Akses Cepat

Lihat di Sumber doi.org/10.1016/j.eswa.2005.09.080

Informasi Jurnal

Tahun Terbit: 2006
Bahasa: en
Total Sitasi: 560×
Sumber Database: Semantic Scholar
DOI: 10.1016/j.eswa.2005.09.080
Akses: Open Access ✓