Adaptive Machine Learning Approach for Emotional Email Classification

Abstract

Emotional e-mail classification is one of the important issues in the service oriented organizations. E-mails are served in a first come first serve basis. Few e-mails express the unfair treatment or dissatisfaction of service. It is essential to serve such e-mails with a high priority. In this paper an attempt is made to identify such mails which express the strong emotions of the customers / stakeholders. This system classifies the e-mails in to three categories via positive, negative and other mails. An adaptive machine learning algorithm that uses combined SVD and KNN methods is developed to solve the problem of emotional e-mail classification. Also an emotional dictionary is used as a central component of this system that serves various emotional words and phrases for classification. The system also adaptive in nature and adapts various new words and phrases that explicates the emotion.

Personalizing University Email toward User Acceptance: An Initial Study

“…The system uses an emotional dictionary that contains descriptive phrases and words as a central component, which is classified by SVD and KNN algorithm. The system is adaptive and could adapt new several words that describe the human emotions [15]. Sethi et al presented a personalized intelligent email system, which arranges emails depending on users' preferences.…”