Improving the Automatic Email Responding System for computer manufacturers via machine learning
Yang Wei-wen, Linchi Kwok · 2012
Computer manufacturers consist of multiple departments, and each department has its own duties and functions. As email is often used as the primary communication tool for computer industries, the customer service departments of the computer manufacturers receive a large number of emails daily. The emails need to be forwarded to the corresponding personnel and processed. Excessive resources and time are spent in manually reading and answering customers' emails. An automatic reply tool is crucial in reducing company resources for manually processing customers' emails. This paper discusses how to improve processing emails automatically for computer manufacturers. Specifically, emails from senders are classified into multiple categories by machine learning algorithms. The reply for each email category is predefined. The Automatic Email Responding System (AERS) replies to an email based on the predefined, corresponding category. This experiment shows that the automatic tool can process and answer emails efficiently.