Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.11851/2030
Full metadata record
DC FieldValueLanguage
dc.contributor.authorGök, Mehmet-
dc.contributor.authorÖzyer, Tansel-
dc.contributor.authorJida, Jamal-
dc.date.accessioned2019-07-10T14:42:47Z
dc.date.available2019-07-10T14:42:47Z
dc.date.issued2015
dc.identifier.citationGök, M., Özyer, T., & Jida, J. (2015, August). A case study for the churn prediction in Turksat internet service subscription. In 2015 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM) (pp. 1220-1224). IEEE.en_US
dc.identifier.isbn978-1-4503-3854-7
dc.identifier.urihttps://dl.acm.org/citation.cfm?doid=2808797.2808821-
dc.identifier.urihttps://hdl.handle.net/20.500.11851/2030-
dc.descriptionIEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM) (2015 : Paris; France)
dc.description.abstractChurn prediction is a customer relationship process that predicts for customers who are at the brink of transferring all the business to competitor. It is predicted by modeling customer behaviors in order to extract patterns. An acquaintance of a customer is more costly than retainment of an existing customer. Churn predictions shed light on members about to leave the service and support promotion activities. These attempts are utilized to avoid subscription cancellation of existing customers. Nowadays, telecommunication companies take churn prediction very serious. They strive for monitoring customers in the business by using various applications in systematic approach. Our study is based on leading internet service providing company, Turksat Satellite Communications and Cable TV Operations Company's customer behavior analysis. It is the leading internet service provider of Turkey operating in telecommunications sector. We have created a two-phase solution utilizing data mining techniques. These are time series clustering and classification techniques.en_US
dc.description.sponsorshipAssociation for Computing Machinery SIGKDD (ACM SIGKDD),CISCO,et al.,IEEE Computer Society,IEEE TCDE,Springer
dc.language.isoenen_US
dc.publisherASSOC Computing Machineryen_US
dc.relation.ispartofProceedings Of The 2015 IEEE/ACM international Conference On Advances in Social Networks Analysis And Mining (ASONAM 2015)en_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectCustomer relationship managementen_US
dc.subjectchurn predictionen_US
dc.subjectdata miningen_US
dc.subjecttime series clusteringen_US
dc.subjectk-means clusteringen_US
dc.subjecthierarchical clusteringen_US
dc.subjectclassificationen_US
dc.subjectsupport vector machinesen_US
dc.subjectrecursive partitioningen_US
dc.titleA Case Study for the Churn Prediction in Turksat Internet Service Subscriptionen_US
dc.typeConference Objecten_US
dc.departmentFaculties, Faculty of Engineering, Department of Computer Engineeringen_US
dc.departmentFakülteler, Mühendislik Fakültesi, Bilgisayar Mühendisliği Bölümütr_TR
dc.identifier.startpage1220
dc.identifier.endpage1224
dc.identifier.wosWOS:000371793500186en_US
dc.identifier.scopus2-s2.0-84962585766en_US
dc.institutionauthorÖzyer, Tansel-
dc.identifier.doi10.1145/2808797.2808821-
dc.authorscopusid8914139000-
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US
item.openairetypeConference Object-
item.languageiso639-1en-
item.grantfulltextnone-
item.fulltextNo Fulltext-
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
item.cerifentitytypePublications-
crisitem.author.dept02.1. Department of Artificial Intelligence Engineering-
Appears in Collections:Bilgisayar Mühendisliği Bölümü / Department of Computer Engineering
Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection
Show simple item record



CORE Recommender

SCOPUSTM   
Citations

1
checked on Dec 21, 2024

WEB OF SCIENCETM
Citations

3
checked on Dec 14, 2024

Page view(s)

130
checked on Dec 23, 2024

Google ScholarTM

Check




Altmetric


Items in GCRIS Repository are protected by copyright, with all rights reserved, unless otherwise indicated.