Essays about: "Trouble Ticket"

Showing result 1 - 5 of 8 essays containing the words Trouble Ticket.

1. 1. Prediction Models for TV Case Resolution Times with Machine Learning

   University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)

   Author : Borja Javierre I Moyano; [2023]
   Keywords : Datasets; Machine Learning ML ; Prediction; Resolution Time RT ; Solve Time; TV Cases; Trouble Tickets TT ; Customer-Related Trouble Tickets Resolution Time; CRM system; BI system; Telecommunications; Dataset; Machine Learning ML ; Prediction; Resolution Time; Solve Time; TV Cases; Trouble Tickets TT ; Kundrelaterade problem Tickets Resolution tid; CRM-system; BI-system; Telekommunikationer.;

   Abstract : TV distribution and stream content delivery of video over the Internet, since is made up of complex networks including Content Delivery Networks (CDNs), cables and end-point user devices, that is very prone to issues appearing in different levels of the network ending up affecting the final customer’s TV services. When a problem affects the customer, and this prevents from having a proper TV delivery service in devices used for stream purposes, the issue is reported through a call, a TV case is opened and the company’s customer handling agents start supervising it to solve the problem as soon as possible. READ MORE

3. 2. Automated Trouble Report Labeling : In The Telecom Industry

   University essay from Uppsala universitet/Institutionen för informationsteknologi

   Author : Bergkvist Alexander; [2022]
   Keywords : Support Ticket labeling;

   Abstract : Trouble reporting is a substantial component in any technical product's maintenance workflow. In this project, we investigated a set of methods for streamlining this workflow, using both software solutions and machine learning. The aim was to find a way of grouping trouble reports for easier analysis and other potential usecases down the line. READ MORE

4. 3. Trouble Tickets resolution time estimation : The Design of a Solution for a Real Case Scenario

   University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)

   Author : Riccardo Colella; [2021]
   Keywords : Trouble Ticket; Resolution Time Estimation; Ticket Resolution; Company processes; Trouble Ticket Management; Telecommunication; Data-Driven; Machine Learning; Problembiljett; uppskattning av lösningstid; lösning av biljetter; företagsprocesser; hantering av problembiljetter; telekommunikation; datadriven; Machine Learning;

   Abstract : Internet Service Providers are companies that deliver services managing a complex network of apparatus and cables. Given the complexity of the network, it often happens that alarms are generated. READ MORE

5. 4. Modeling Trouble Ticket ResolutionTime Using Machine Learning

   University essay from Linköpings universitet/Statistik och maskininlärning

   Author : Asad Enver; [2021]
   Keywords : Machine Learning;

   Abstract : This thesis work, conducted at Telenor Sweden, aims to build a model that would try to accurately predict the resolution time of Priority 4 Trouble Tickets. (Priority 4 trouble tickets are those tickets that get generated more often-e in higher volumes per month). READ MORE

6. 5. Telecommunications Trouble Ticket Resolution Time Modelling with Machine Learning

   University essay from KTH/Matematisk statistik

   Author : Axel Björling; [2021]
   Keywords : Machine learning; regression; classification; telecommunications trouble ticket resolution time; support vector machine; logistic regression; deep neural network; gradient boosted trees regression; Maskininlärning; regression; klassificering; avvikelserapport i telenät; lösningstid felanmälan; support vector machine; logistic regression; neurala nätverk; gradient boosted trees regression;

   Abstract : This report explores whether machine learning methods such as regression and classification can be used with the goal of estimating the resolution time of trouble tickets in a telecommunications network. Historical trouble ticket data from Telenor were used to train different machine learning models. READ MORE