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dc.contributor.authorAlShourbaji, Ibrahim
dc.contributor.authorHelian, Na
dc.contributor.authorSun, Yi
dc.contributor.authorAlhameed, Mohammed
dc.date.accessioned2021-09-17T15:45:02Z
dc.date.available2021-09-17T15:45:02Z
dc.date.issued2021-01-01
dc.identifier.citationAlShourbaji , I , Helian , N , Sun , Y & Alhameed , M 2021 , ' Customer Churn Prediction in Telecom Sector: A Survey and way a head ' , International Journal of Scientific & Technology Research (IJSTR) , vol. 10 , no. 1 , pp. 388-399 . < https://www.ijstr.org/final-print/jan2021/Customer-Churn-Prediction-In-Telecom-Sector-A-Survey-And-Way-A-Head.pdf >
dc.identifier.issn2277-8616
dc.identifier.otherORCID: /0000-0001-6687-0306/work/100133168
dc.identifier.urihttp://hdl.handle.net/2299/25060
dc.description© 2021 International Journal of Scientific & Technology Research. This work is licensed under a Creative Commons Attribution 4.0 International License.
dc.description.abstractThe telecommunication (telecom)industry is a highly technological domain has rapidly developed over the previous decades as a result of the commercial success in mobile communication and the internet. Due to the strong competition in the telecom industry market, companies use a business strategy to better understand their customers’ needs and measure their satisfaction. This helps telecom companies to improve their retention power and reduces the probability to churn. Knowing the reasons behind customer churn and the use of Machine Learning (ML) approaches for analyzing customers' information can be of great value for churn management. This paper aims to study the importance of Customer Churn Prediction (CCP) and recent research in the field of CCP. Challenges and open issues that need further research and development to CCP in the telecom sector are exploreden
dc.format.extent12
dc.format.extent591516
dc.language.isoeng
dc.relation.ispartofInternational Journal of Scientific & Technology Research (IJSTR)
dc.subjectCustomer churn
dc.subjectprediction
dc.subjectmachine learning,
dc.subjectchurn management
dc.subjecttelecom
dc.titleCustomer Churn Prediction in Telecom Sector: A Survey and way a headen
dc.contributor.institutionCentre for Computer Science and Informatics Research
dc.contributor.institutionSchool of Physics, Engineering & Computer Science
dc.contributor.institutionDepartment of Computer Science
dc.contributor.institutionBiocomputation Research Group
dc.description.statusPeer reviewed
dc.identifier.urlhttps://www.ijstr.org/final-print/jan2021/Customer-Churn-Prediction-In-Telecom-Sector-A-Survey-And-Way-A-Head.pdf
rioxxterms.typeJournal Article/Review
herts.preservation.rarelyaccessedtrue


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