Email Classification into Relevant Category Using Neural Networks

TL;DR

This paper proposes an artificial neural network model to classify customer emails into relevant categories, aiming to improve departmental sorting efficiency in service providers handling large volumes of emails.

Contribution

The paper introduces a neural network-based approach specifically designed for email categorization, tested on personal Gmail datasets, addressing a practical text classification challenge.

Findings

Neural network achieved high accuracy in email categorization.

Effective handling of large-scale email datasets demonstrated.

Potential for real-world application in customer service automation.

Abstract

In the real world, many online shopping websites or service provider have single email-id where customers can send their query, concern etc. At the back-end service provider receive million of emails every week, how they can identify which email is belonged of a particular department? This paper presents an artificial neural network (ANN) model that is used to solve this problem and experiments are carried out on user personal Gmail emails datasets. This problem can be generalised as typical Text Classification or Categorization.