Open AccessAn approach to email categorization and response generation
Author(s) -
Saša Arsovski,
Muniru Idris Oladele,
Adrian David Cheok,
Velibor Premčevski,
Branko Markoski
Publication year - 2022
Publication title -
computer science and information systems
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.244
H-Index - 24
eISSN - 2406-1018
pISSN - 1820-0214
DOI - 10.2298/csis211101009a
Subject(s) - computer science , categorization , novelty , chatbot , markup language , ambiguity , artificial intelligence , natural language processing , artificial neural network , information retrieval , xml , world wide web , philosophy , theology , programming language
The creation of automatic e-mail responder systems with human-quality responses is challenging due to the ambiguity of meanings and difficulty in response modeling. In this paper, we present the Personal Email Responder (PER); a novel system for email categorization and semi-automatic response generation. The key novelty presented in this paper is an approach to email categorization that distinguishes query and non-query email messages using Natural Language Processing (NLP) and Neural Network (NN) methods. The second novelty is the use of Artificial Intelligence Markup Language (AIML)-based chatbot for semiautomatic response creation. The proposed methodology was implemented as a prototype mobile application, which was then used to conduct an experiment. Email messages logs collected in the experimental phase are used to evaluate the proposed methodology and estimate the accuracy of the presented system for email categorization and semi-automatic response generation.