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

Kraidet Khowongprasoed, Taravichet Titijaroonroj
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引用次数: 1

Abstract

Ticket 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.
IT基础设施公司使用机器学习的自动泰国票务分类
票据分类是在分配解决方案团队为每个票据服务之前定义每个票据的类别名称的过程。支持公司内外的客户是一个重要的过程。如果处理时间过长或延迟,会使客户不满意。根据研究公司2019-2021年的记录数据,我们发现由于办公室工作人员的误解,人工票据分类的错误率约为53%。为了解决这一问题,我们提出了一种基于支持向量机的词频率-逆文档频率的泰国票务自动分类方法。实验结果表明,该方法的分类性能比人工分类提高了2倍,达到41%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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