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Fuzzy recommendations in marketing campaigns
Blekinge Institute of Technology, Faculty of Computing, Department of Computer Science and Engineering.
Blekinge Institute of Technology, Faculty of Computing, Department of Computer Science and Engineering.
Telenor, SWE.
Blekinge Institute of Technology, Faculty of Computing, Department of Computer Science and Engineering.
Show others and affiliations
2017 (English)In: Communications in Computer and Information Science / [ed] Darmont J.,Kirikova M.,Norvag K.,Wrembel R.,Papadopoulos G.A.,Gamper J.,Rizzi S., Springer, 2017, Vol. 767, p. 246-256Conference paper, Published paper (Refereed)
Abstract [en]

The population in Sweden is growing rapidly due to immigration. In this light, the issue of infrastructure upgrades to provide telecommunication services is of importance. New antennas can be installed at hot spots of user demand, which will require an investment, and/or the clientele expansion can be carried out in a planned manner to promote the exploitation of the infrastructure in the less loaded geographical zones. In this paper, we explore the second alternative. Informally speaking, the term Infrastructure-Stressing describes a user who stays in the zones of high demand, which are prone to produce service failures, if further loaded. We have studied the Infrastructure-Stressing population in the light of their correlation with geo-demographic segments. This is motivated by the fact that specific geo-demographic segments can be targeted via marketing campaigns. Fuzzy logic is applied to create an interface between big data, numeric methods for its processing, and a manager who wants a comprehensible summary. © 2017, Springer International Publishing AG.

Place, publisher, year, edition, pages
Springer, 2017. Vol. 767, p. 246-256
Keywords [en]
Call detail records, Fuzzy membership function, Geo-demographic segments, Intelligent data mining, Marketing
National Category
Computer Sciences
Identifiers
URN: urn:nbn:se:bth-15307DOI: 10.1007/978-3-319-67162-8_24Scopus ID: 2-s2.0-85029801359ISBN: 9783319671611 (print)OAI: oai:DiVA.org:bth-15307DiVA, id: diva2:1147593
Conference
21st European Conference on Advances in Databases and Information Systems, ADBIS, Nicosia
Part of project
Bigdata@BTH- Scalable resource-efficient systems for big data analytics, Knowledge FoundationAvailable from: 2017-10-06 Created: 2017-10-06 Last updated: 2024-09-25Bibliographically approved

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Lundberg, LarsRosander, OliverSidorova, Yulia

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Podapati, SasidahrLundberg, LarsRosander, OliverSidorova, Yulia
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CiteExportLink to record
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  • apa
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