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

Singh, Samneet; Liu, Yan LU ; Ding, Wayne and Li, Zheng LU (2016) 5th IEEE International Congress on Big Data, BigData Congress 2016 In Proceedings - 2016 IEEE International Congress on Big Data, BigData Congress 2016 p.283-290
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... (More)

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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Please use this url to cite or link to this publication:
author
organization
publishing date
type
Chapter in Book/Report/Conference proceeding
publication status
published
subject
keywords
Big data, Data mining workflow, Empirical evaluation, Telecom service
in
Proceedings - 2016 IEEE International Congress on Big Data, BigData Congress 2016
pages
8 pages
publisher
Institute of Electrical and Electronics Engineers Inc.
conference name
5th IEEE International Congress on Big Data, BigData Congress 2016
external identifiers
  • scopus:84994613807
ISBN
9781509026227
DOI
10.1109/BigDataCongress.2016.43
language
English
LU publication?
yes
id
986ad26b-e633-4b99-8613-075bbca2aa1a
date added to LUP
2016-12-07 12:13:32
date last changed
2017-08-27 06:31:06
@inproceedings{986ad26b-e633-4b99-8613-075bbca2aa1a,
  abstract     = {<p>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.</p>},
  author       = {Singh, Samneet and Liu, Yan and Ding, Wayne and Li, Zheng},
  booktitle    = {Proceedings - 2016 IEEE International Congress on Big Data, BigData Congress 2016},
  isbn         = {9781509026227},
  keyword      = {Big data,Data mining workflow,Empirical evaluation,Telecom service},
  language     = {eng},
  month        = {10},
  pages        = {283--290},
  publisher    = {Institute of Electrical and Electronics Engineers Inc.},
  title        = {Evaluation of data mining tools for telecommunication monitoring data using design of experiment},
  url          = {http://dx.doi.org/10.1109/BigDataCongress.2016.43},
  year         = {2016},
}