Knowledge Discovery from Trouble Ticketing Reports in a Large Telecommunication Company

This paper describes the work developed by Telefonica I+D about an application of advanced data mining, text mining and machine learning techniques for the study of the network elements failures managed by the trouble ticketing system of a large telecommunication company, in order to be able to analyze, prioritize and, in some cases, solve without human intervention the huge amount of trouble reports to be managed. Furthermore, this paper will present the techniques used for its achievement, as well as the results obtained so far, showing how these techniques may help important companies to save plenty of time and resources in fault management, improving the service quality.