Novosibirsk State University Journal of Information Technologies|
ISSN 2410-0420 (Online), ISSN 1818-7900 (Print)
Big Data Usage in Subscribers Routes Constructing by Mobile Operators
The article observes general questions and variants of big data usage in commercial enterprises, particularly in telecommunications. The problem of big data functional is discussed, and the approach of this functional as well. The author makes an accent on the certain problem of the cell operator, that can be solved with the help of data, the company has at its disposal. He analyzes and constructs most popular clients’ routes during certain days to optimize advertizing placement and increase the effect of advertisement campaigns. The author identifies those route clusters, that show the most successful results
big data, telecommunications, cell operator, mobile, routes, graphs, optimization, advertisement placement, clusters, advertisement campaigns
How to cite:
Ponomarev A. A. Big Data Usage in Subscribers Routes Constructing by Mobile Operators // Vestnik NSU Series: Information Technologies. - 2017. - Volume 15, Issue No 1. - P. 70-78. - ISSN 1818-7900. (in Russian).
Full Text in Russian
Available in PDF
1. Nevostruev K. N. Literature Review of Machine Learning Methods (Machine Learning). Computer Instruments in Education, 2015, no. 4, p. 19–26. (in Russ.)
2. Ponomarev A. Big data usage in telecommunications. Computer Instruments in Education, 2015, no. 4. URL: http://ipo.spb.ru/journal/index.php?article/1781/ (Application Date 25.01.2017).
3. Laasonen Kari. Clustering and Prediction of Mobile User Routes from Cellular Data. Knowledge Discovery in Databases: PKDD, 2005, p. 569–576.
4. Leskovec J. A., Rajaraman J.D. Ullman. Mining of Massive Datasets. Cambridge University Press, 2011.
Main title Vestnik NSU Series: Information Technologies, Volume 15, Issue No 1 (2017).
Parallel title: Novosibirsk State University Journal of Information Technologies Volume 15, Issue No 1 (2017).
Key title: Vestnik Novosibirskogo gosudarstvennogo universiteta. Seriâ: Informacionnye tehnologii
Abbreviated key title: Vestn. Novosib. Gos. Univ., Ser.: Inf. Tehnol.
Variant title: Vestnik NGU. Seriâ: Informacionnye tehnologii
Year of Publication: 2017
ISSN: 1818-7900 (Print), ISSN 2410-0420 (Online)
Publisher: Novosibirsk State University Press
© 2006-2018, Novosibirsk State University.