Knowledge Discovery from Trouble Ticketing Reports in a Large Telecommunication Company

  • Authors:
  • Yaiza Temprado;Francisco Javier Molinero;Carolina Garcia;Julia Gomez

  • Affiliations:
  • -;-;-;-

  • Venue:
  • CIMCA '08 Proceedings of the 2008 International Conference on Computational Intelligence for Modelling Control & Automation
  • Year:
  • 2008

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Abstract

This paper describes the work developed byTelefónica I+D about an application of advanced DataMining, Text Mining and Machine Learning techniquesfor the study of the network elements failures managedby the Trouble Ticketing System of a largetelecommunication company, in order to be able toanalyze, prioritize and, in some cases, solve withouthuman intervention the huge amount of trouble reportsto be managed. Furthermore, this paper will presentthe techniques used for its achievement, as well as theresults obtained so far, showing how these techniquesmay help important companies to save plenty of timeand resources in fault management, improving theservice quality.