Supporting Telecommunication Alarm Management System With Trouble Ticket Prediction

Processing customer support requests via a support ticket system is a key-element for companies to provide support to their customers in an organized and professional way. However, distributing and processing such tickets is much work, increasing the cost for the support providing company and stretching the resolution time. The advancing potential of Machine Learning has led to the goal of automating those support ticket systems. Against this background, we conducted a Literature Review aiming at determining the present state-of-the-art technology in the field of automated support ticket systems. We provide an overview about present trends and topics discussed in this field. During the Literature Review, we found creating an automated incident management tool being the majority topic in the field followed by request escalation and customer sentiment prediction and identified Random Forrest and Support Vector Machine as best performing algorithms for classification in the field.

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“…Asres, Mengistu [17] x x Nayak, Rai [15] x x Yang [18] x Amin, Lancaster [19] (x) Baresi, Quattrocchi [20] x x…”

Section: Sent Pred Othermentioning

confidence: 99%

“…In most cases, a practical use case was on hand, such that the authors mainly developed such an artifact for or optimized an existing one in a distinct situation (for example in [1]; [8]; [6]; [29]; or [17]). This of course leads to a problem of generalizing their results as already ascertained by Misra and Podder [27].…”

Section: Incident Management Toolmentioning

confidence: 99%