Automatic Thai Ticket Classification By Using Machine Learning For IT Infrastructure Company

dc.contributor.authorKraidet Khowongprasoed
dc.contributor.authorTaravichet Titijaroonroj
dc.date.accessioned2026-05-08T19:20:17Z
dc.date.issued2022-6-22
dc.description.abstractTicket classification is a process to define the category name of each ticket before assigning the resolution team to serve each ticket. It is an important process to support the customers inside and outside the company. It can make customer dissatisfaction if the processing time is high or delayed. Based on the recording data in 2019-2021 at the studying company, we found that the manual ticket classification got an error rate about 53 percent because the office workers misunderstand. To alleviate this problem, we propose the methodology for automatic Thai ticket classification by using Term Frequency-Inverse Document Frequency with Support Vector Machine. The experimental result shows that the performance of the proposed methodology is higher than the manual classification by 2 times or 41 percent.
dc.identifier.doi10.1109/jcsse54890.2022.9836250
dc.identifier.urihttps://dspace.kmitl.ac.th/handle/123456789/17457
dc.subjectText and Document Classification Technologies
dc.subjectImbalanced Data Classification Techniques
dc.subjectWeb Data Mining and Analysis
dc.titleAutomatic Thai Ticket Classification By Using Machine Learning For IT Infrastructure Company
dc.typeArticle

Files

Collections