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Feasibility of using network support data to predict risk level of trouble tickets
Linköping University, Department of Computer and Information Science, Software and Systems.
2016 (English)Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
Abstract [en]

Internet Service Providers gather vast amounts of data in the form of trouble tickets created from connectivity related issues. This data is often stored and seldom used for proactive purposes. This thesis explores the feasibility of finding correlations in network support data through the use of data mining activities. Correlations such as these could be used for improving troubleshooting or staffing related activities. The approach uses the data mining methodology CRISP-DM to investigate typical data mining operations from the perspective of a Network Operation Center. The results show that correlations between the solving time and other ticket related attributes do exist and that support data could be used for the activities mentioned. The results also show that it exists a lot of room for improvement when it comes to data mining activities in network support data.

Place, publisher, year, edition, pages
2016. , 72 p.
Keyword [en]
Network support data, Risk level, Machine learning
National Category
Computer Systems
URN: urn:nbn:se:liu:diva-128656ISRN: LIU-IDA/LITH-EX-A--16/016--SEOAI: diva2:931210
External cooperation
TeliaSonera AB
Subject / course
Computer science
2016-05-02, John von Neumann, 13:15 (Swedish)
Available from: 2016-06-07 Created: 2016-05-26 Last updated: 2016-06-07Bibliographically approved

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