Deep Learning based Intelligent E-mail Autoresponder

Author:

Lakshmi Priya B.,Jayalakshmy S.,Saraswathi D.,Kumar V.,Dinesh E.

Abstract

Abstract Handling huge volume of emails is a very challenging task in the customer support applications and an automated email responding system will be of great help. In this paper, an intelligent email autoresponder system is developed which either attempts to respond to the incoming emails from various category of customers or generate token for service request to address the issue manually by an expert member. First, based on the content the system has to predict whether the mail belong to the category of auto responding or to invoke a service request. This classification of email is carried out using long short term (LSTM) and bi-directional LSTM networks (Bi-LSTM) networks and the classification performance is analyzed. The results presented in this work show that the Bi-LSTM classifier outperforms LSTM network.

Publisher

IOP Publishing

Subject

General Physics and Astronomy

Reference10 articles.

1. Text Document Preprocessing with the Bayes Formula for Classification Using the Support Vector Machine;Isa;IEEE Transactions on Knowledge and Data Engineering,2008

2. A Framework for Learning Comprehensible Theories in XML Document Classification;Wu;IEEE Transactions on Knowledge and Data Engineering,2012

3. Alecsa: attentive learning for email categorization using structural aspects;Dehghani;Knowledge-Based Systems,2016

4. Semi-supervised text classification with universum learning;Liu;IEEE transactions on cybernetics,2015

5. Classification of text documents based on score level fusion approach;Bhushan;Pattern Recognition Letters,2017

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