TY - THES ID - 146388199 TI - Travail de fin d'études et stage[BR]- Travail de fin d'études : Natural language processing for automated Service Desk incident routing[BR]- Stage d'insertion professionnelle AU - Debbali, Imane AU - Louppe, Gilles AU - Lion, Pascal AU - Cornélusse, Bertrand AU - Sutera, Antonio PY - 2020 PB - Liège Université de Liège (ULiège) DB - UniCat KW - Machine learning KW - Natural language processing KW - python KW - automation KW - service desk KW - Ingénierie, informatique & technologie > Sciences informatiques UR - https://www.unicat.be/uniCat?func=search&query=sysid:146388199 AB - Automation is happening in all aspects of our daily lives. This work aims at improving the efficiency of NRB Service Desk thanks to machine learning and natural language processing by automating the routing of incidents tickets. This is mainly done by analysing the ticket textual content. Machine learning classifiers is compared after putting the data into the right shape. The logistic regression performed the best followed by SVM. In the end, a short study with deep learning is carried. ER -