Evaluation of data mining tools for telecommunication monitoring data using design of experiment

Samneet Singh; Yan Liu; Wayne Ding; Zheng Li

doi:10.1109/BigDataCongress.2016.43

Evaluation of data mining tools for telecommunication monitoring data using design of experiment

Samneet Singh
, Yan Liu
, Wayne Ding
, Zheng Li

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

5 Citations (Scopus)

Abstract

Telecommunication monitoring data requires the automation of data analysis workflows. A data mining tool provides data workflow management systems to process and perform analysis tasks. This paper presents an evaluation of two example data mining tools following the principles of design of experiment (DOE) to run forecasting and clustering workflows for telecom monitoring data. We conduct both quantitative and qualitative evaluation on datasets collected from a trial mobile network. The datasets consist of 1 month, six months, one year and two years of time frames that provide the average number of connected users per cell on base stations. The observations from this evaluation provide insights of each data mining tool in the context of data analysis workflows. This documented design of experiment will further facilitate replicating this evaluation study and evaluate other data mining tools.

Original language	English
Title of host publication	Proceedings of the 2016 IEEE International Congress on Big Data (BigData Congress)
Editors	Calton Pu, Geoffrey Fox, Ernesto Damiani
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	283-290
Number of pages	8
ISBN (Electronic)	9781509026227
ISBN (Print)	9781509026234
DOIs	https://doi.org/10.1109/BigDataCongress.2016.43
Publication status	Published - 06 Oct 2016
Externally published	Yes
Event	5th IEEE International Congress on Big Data, BigData Congress 2016 - San Francisco, United States Duration: 27 Jun 2016 → 02 Jul 2016

Publication series

Name	Proceedings of the IEEE International Congress on Big Data (BigData Congress)

Conference

Conference	5th IEEE International Congress on Big Data, BigData Congress 2016
Country/Territory	United States
City	San Francisco
Period	27/06/2016 → 02/07/2016

Bibliographical note

Publisher Copyright:
© 2016 IEEE.

Keywords

Big data
Data mining workflow
Empirical evaluation
Telecom service

ASJC Scopus subject areas

Information Systems
Computer Science Applications
Information Systems and Management

Access to Document

10.1109/BigDataCongress.2016.43Licence: Unspecified

Cite this

Singh, S., Liu, Y., Ding, W., & Li, Z. (2016). Evaluation of data mining tools for telecommunication monitoring data using design of experiment. In C. Pu, G. Fox, & E. Damiani (Eds.), Proceedings of the 2016 IEEE International Congress on Big Data (BigData Congress) (pp. 283-290). Article 7584949 (Proceedings of the IEEE International Congress on Big Data (BigData Congress)). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/BigDataCongress.2016.43

Singh, Samneet ; Liu, Yan ; Ding, Wayne et al. / Evaluation of data mining tools for telecommunication monitoring data using design of experiment. Proceedings of the 2016 IEEE International Congress on Big Data (BigData Congress). editor / Calton Pu ; Geoffrey Fox ; Ernesto Damiani. Institute of Electrical and Electronics Engineers Inc., 2016. pp. 283-290 (Proceedings of the IEEE International Congress on Big Data (BigData Congress)).

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title = "Evaluation of data mining tools for telecommunication monitoring data using design of experiment",

abstract = "Telecommunication monitoring data requires the automation of data analysis workflows. A data mining tool provides data workflow management systems to process and perform analysis tasks. This paper presents an evaluation of two example data mining tools following the principles of design of experiment (DOE) to run forecasting and clustering workflows for telecom monitoring data. We conduct both quantitative and qualitative evaluation on datasets collected from a trial mobile network. The datasets consist of 1 month, six months, one year and two years of time frames that provide the average number of connected users per cell on base stations. The observations from this evaluation provide insights of each data mining tool in the context of data analysis workflows. This documented design of experiment will further facilitate replicating this evaluation study and evaluate other data mining tools.",

keywords = "Big data, Data mining workflow, Empirical evaluation, Telecom service",

author = "Samneet Singh and Yan Liu and Wayne Ding and Zheng Li",

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language = "English",

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series = "Proceedings of the IEEE International Congress on Big Data (BigData Congress)",

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Singh, S, Liu, Y, Ding, W & Li, Z 2016, Evaluation of data mining tools for telecommunication monitoring data using design of experiment. in C Pu, G Fox & E Damiani (eds), Proceedings of the 2016 IEEE International Congress on Big Data (BigData Congress)., 7584949, Proceedings of the IEEE International Congress on Big Data (BigData Congress), Institute of Electrical and Electronics Engineers Inc., pp. 283-290, 5th IEEE International Congress on Big Data, BigData Congress 2016, San Francisco, United States, 27/06/2016. https://doi.org/10.1109/BigDataCongress.2016.43

Evaluation of data mining tools for telecommunication monitoring data using design of experiment. / Singh, Samneet; Liu, Yan; Ding, Wayne et al.
Proceedings of the 2016 IEEE International Congress on Big Data (BigData Congress). ed. / Calton Pu; Geoffrey Fox; Ernesto Damiani. Institute of Electrical and Electronics Engineers Inc., 2016. p. 283-290 7584949 (Proceedings of the IEEE International Congress on Big Data (BigData Congress)).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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AU - Ding, Wayne

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AB - Telecommunication monitoring data requires the automation of data analysis workflows. A data mining tool provides data workflow management systems to process and perform analysis tasks. This paper presents an evaluation of two example data mining tools following the principles of design of experiment (DOE) to run forecasting and clustering workflows for telecom monitoring data. We conduct both quantitative and qualitative evaluation on datasets collected from a trial mobile network. The datasets consist of 1 month, six months, one year and two years of time frames that provide the average number of connected users per cell on base stations. The observations from this evaluation provide insights of each data mining tool in the context of data analysis workflows. This documented design of experiment will further facilitate replicating this evaluation study and evaluate other data mining tools.

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Singh S, Liu Y, Ding W, Li Z. Evaluation of data mining tools for telecommunication monitoring data using design of experiment. In Pu C, Fox G, Damiani E, editors, Proceedings of the 2016 IEEE International Congress on Big Data (BigData Congress). Institute of Electrical and Electronics Engineers Inc. 2016. p. 283-290. 7584949. (Proceedings of the IEEE International Congress on Big Data (BigData Congress)). doi: 10.1109/BigDataCongress.2016.43

Evaluation of data mining tools for telecommunication monitoring data using design of experiment

Abstract

Publication series

Conference

Bibliographical note

Keywords

ASJC Scopus subject areas

Access to Document

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Cite this