Location Analytics for Churn Service Type Prediction


Tan, Nicholas Yu Zhe and Ting, Choo Yee and Ho, Chuing Ching (2020) Location Analytics for Churn Service Type Prediction. In: Computational Science and Technology. Lecture Notes in Electrical Engineering (Computational Science and Technology), 603 . Springer Verlag, pp. 709-718. ISBN 9789811500572

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Churn has always been a challenge for companies that trade products or services. Research work has been focusing on predicting customer churn, however, the relationship between churn and geospatial information have not been fully explored. In this work, it was hypothesized that geospatial information exhibits a correlation with churn pattern. Empirical study was conducted to employ five different similarity algorithms to investigate the similarity between one churn location to others. The findings suggested that location features do assert a positive effect on customer churn with the accuracy of 70.24% using Hamming algorithm based on top 31 rows of majority voting.

Item Type: Book Section
Uncontrolled Keywords: Wireless localization, Location analytics, Churn, Prediction
Subjects: T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK5101-6720 Telecommunication. Including telegraphy, telephone, radio, radar, television
Divisions: Faculty of Computing and Informatics (FCI)
Depositing User: Ms Suzilawati Abu Samah
Date Deposited: 16 Dec 2020 10:04
Last Modified: 16 Dec 2020 10:05
URII: http://shdl.mmu.edu.my/id/eprint/7947


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