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Finding a healthy equilibrium of geo-demographic segments for a telecom business: Who are malicious hot-spotters?
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.ORCID iD: 0000-0001-9947-1088
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2019 (English)In: Machine Learning Paradigms: Advances in Data Analytics / [ed] George A. Tsihrintzis, Dionisios N. Sotiropoulos, Lakhmi C. Jain, Springer Science and Business Media Deutschland GmbH , 2019, p. 187-196Chapter in book (Refereed)
Abstract [en]

In telecommunication business, a major investment goes into the infrastructure and its maintenance, while business revenues are proportional to how big, good, and well-balanced the customer base is. In our previous work we presented a data-driven analytic strategy based on combinatorial optimization and analysis of the historical mobility designed to quantify the desirability of different geo-demographic segments, and several segments were recommended for a partial reduction. Within a segment, clients are different. In order to enable intelligent reduction, we introduce the term infrastructure-stressing client and, using the proposed method, we reveal the list of the IDs of such clients. We also have developed a visualization tool to allow for manual checks: it shows how the client moved through a sequence of hot spots and was repeatedly served by critically loaded antennas. The code and the footprint matrix are available on the SourceForge. © 2019, Springer International Publishing AG, part of Springer Nature.

Place, publisher, year, edition, pages
Springer Science and Business Media Deutschland GmbH , 2019. p. 187-196
Series
Intelligent Systems Reference Library, ISSN 1868-4394 ; 149
Keywords [en]
Business intelligence, Combinatorial optimization, Fuzzy logic, Geo-demographic segments, Mobility data, MOSAIC
National Category
Telecommunications Business Administration Computer Sciences
Identifiers
URN: urn:nbn:se:bth-16885DOI: 10.1007/978-3-319-94030-4_8Scopus ID: 2-s2.0-85049522294ISBN: 978-3-319-94029-8 (print)OAI: oai:DiVA.org:bth-16885DiVA, id: diva2:1239961
Available from: 2018-08-20 Created: 2018-08-20 Last updated: 2018-08-20Bibliographically approved

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Sidorova, YuliaGrahn, HåkanLundberg, Lars

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