论文标题
量身定制的帮助台自动修复的问题分类
Problem Classification for Tailored Helpdesk Auto-Replies
论文作者
论文摘要
它的帮助演奏者承担了快速响应用户查询的任务。为了使用户对自己的查询重要的信心，服务台将自动向用户自动查询，并确认已收到并记录了他们的查询。此自动重复可能包括通用的“锅炉板”文本，该文本解决了当天的常见问题以及相关信息和链接。此处探索的方法是将自动 - 重新调整的内容量身定制为用户的问题，以提高所包括信息的相关性。通过在适当的IT帮助台电子邮件数据上训练神经网络来实现问题分类。虽然这不能代替HelpDesk代理商的后续行动，但目的是该系统将提供实用的定格间隙。
IT helpdesks are charged with the task of responding quickly to user queries. To give the user confidence that their query matters, the helpdesk will auto-reply to the user with confirmation that their query has been received and logged. This auto-reply may include generic `boiler-plate' text that addresses common problems of the day, with relevant information and links. The approach explored here is to tailor the content of the auto-reply to the user's problem, so as to increase the relevance of the information included. Problem classification is achieved by training a neural network on a suitable corpus of IT helpdesk email data. While this is no substitute for follow-up by helpdesk agents, the aim is that this system will provide a practical stop-gap.
