Intelligent email summarisation system (IESS)

T. Ayodele, Shikun Zhou, R. Khusainov
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Abstract

Many email users, especially business men, managers and academician receive many email messages that require sorting out within a short period of time. While most mail summarisation applications allow dialogue structure of emails, users to summarise messages into percentages or numbers of sentences. In practice this task tends to be tedious and solutions available today often require programming skills on the part of the email users. The users define rules for summarising messages. For each message, the user must first decide which message is most important. Then, the user must inform the mail summariser of that choice by selecting the appropriate icon or menu item from among what is typically a set of several dozen choices. The combined effort of choosing a message and conveying that choice to the application often discourages users from summarising their mails, resulting in unmanageable inboxes that contain hundreds or even thousands of un-précised and unnecessary messages. Intelligent email summarisation system (IESS), encourages users to have summative messages by simplifying the content of the mail. Using unsupervised machine learning techniques in combination with automated word and phrases modeller to intelligently provide a précis summary of each email messages is developed to reduce the burden of email users.
智能邮件摘要系统(IESS)
许多电子邮件用户,尤其是商务人士、管理人员和院士,会收到许多需要在短时间内整理的电子邮件。虽然大多数邮件摘要应用程序允许邮件的对话结构,但用户可以将消息摘要为百分比或句子数。在实践中,这项任务往往是乏味的,而且目前可用的解决方案通常需要电子邮件用户的编程技能。用户定义汇总消息的规则。对于每条消息,用户必须首先决定哪条消息是最重要的。然后,用户必须通过从通常有几十个选项的一组中选择适当的图标或菜单项来通知邮件摘要器该选择。选择消息并将该选择传递给应用程序的综合工作通常会阻止用户总结他们的邮件,从而导致无法管理的收件箱,其中包含数百甚至数千条未处理的和不必要的消息。智能电子邮件摘要系统(IESS),通过简化邮件内容,鼓励用户使用摘要信息。利用无监督机器学习技术结合自动单词和短语建模器,智能地提供每个电子邮件消息的概要,以减轻电子邮件用户的负担。
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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