The aim here is to explore the methods to automate the labelling of the information that is present in bug trackers and
client support systems. This is majorly based on the classification of the content depending on some criteria e.g., priority or
product area. Labelling of the tickets is important as it helps in effective and efficient handling of the ticket and help is quicker
and comprehensive resolution of the tickets. The main goal of the project is to analyze the existing methodologies used for
automated labelling and then use a newer approach and compare the results. The existing methodologies are the ones which are
based of the neural networks and without neural networks. In this project, a newer approach based on the recurrent neural
networks which are based on the hierarchical attention paradigm will be used.
