Design and Implementation of an AI-Based Email Filtering and Prioritization System for Polytechnic Administration Efficiency

Publication Details

Publication Date

10/10/2026

Volume / Issue

Vol 1, Issue 5 (2026)

Article No.

013

Journal

British Journal of Contemporary Research

DOI

https://doi.org/10.67693/BJCR-2MS4QGNE

Received

17 Jul 2026

Views

24

Downloads

13

Abstract

The rapid growth of electronic communication within higher education institutions has significantly increased the volume of emails processed by administrative personnel. Consequently, critical institutional communications are often overlooked among routine messages, promotional content, and spam, resulting in communication delays, reduced productivity, and administrative inefficiencies. This study presents the design and implementation of an Artificial Intelligence (AI)-based email filtering and prioritization system tailored for polytechnic administrative environments. The proposed framework integrates Natural Language Processing (NLP) and supervised machine learning algorithms to classify incoming emails into Urgent, Actionable, Routine, Promotional, and Spam categories. Multiple classification algorithms, including Naïve Bayes, Support Vector Machine (SVM), Random Forest, and DistilBERT, were evaluated to determine optimal performance for institutional communication datasets. The system incorporates contextual prioritization mechanisms, role-based access controls, audit logging, and a web-based dashboard for real-time communication management. Findings indicate that intelligent email prioritization can significantly improve communication responsiveness, reduce email overload, and support digital transformation initiatives in tertiary institutions. The study contributes to a scalable framework suitable for deployment across Nigerian polytechnics and other public-sector organizations.

License

This article is published under the Creative Commons Attribution 4.0 International License . Free to read, share, and adapt with attribution.