DocumentCode :
1967478
Title :
Customer Churn Prediction for Telecom Services
Author :
Yabas, Utku ; Cankaya, Hakki Candan ; Ince, Turker
Author_Institution :
Sch. of Eng. & Comput. Sci., Izmir Univ. of Econ., Izmir, Turkey
fYear :
2012
fDate :
16-20 July 2012
Firstpage :
358
Lastpage :
359
Abstract :
Customer churn is a big concern for telecom service providers due to its associated costs. This short paper briefly explains our ongoing work on customer churn prediction for telecom services. We are working on data mining methods to accurately predict customers who will change and turn to another provider for the same or similar service. Sample dataset we use for our experiments has been compiled by Orange Telecom from real data. They posted the sample dataset for 2009 Knowledge Discovery and Data Mining Competition. IBM has scored the highest on this dataset requiring significant amount of computational resources. We are aiming to find alternative methods that can match or improve the recorded highest score with more efficient use of resources. Dataset has very large number of features, examples and incomplete values. As the first step, we employ some methods to preprocess the dataset for its imperfections. Then, we compare and contrast various ensemble and single classifiers. We conclude the paper with future directions for the study.
Keywords :
data mining; signal classification; telecommunication services; IBM; Orange Telecom; associated costs; computational resources; customer churn prediction; data mining competition; knowledge discovery; single classifiers; telecom service providers; Data mining; Decision trees; Educational institutions; Prediction algorithms; Telecommunication services; Vegetation; churn prediction; data mining; machine learning; pattern recognition;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computer Software and Applications Conference (COMPSAC), 2012 IEEE 36th Annual
Conference_Location :
Izmir
ISSN :
0730-3157
Print_ISBN :
978-1-4673-1990-4
Electronic_ISBN :
0730-3157
Type :
conf
DOI :
10.1109/COMPSAC.2012.54
Filename :
6340176
Link To Document :
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