Enhancing email urgency reply prediction with ATAN-Transformer Fusion

In the contemporary landscape of burgeoning email communication, effective sorting and prioritization present formidable challenges. Precise prediction of email urgency is pivotal for efficient email management. Our study addresses this challenge by automating the critical process using advanced machine learning and deep learning algorithms. We introduce the Adaptive Temporal Attention Transformer Fusion (ATATFUSION), a novel methodology meticulously crafted to cater to the delicate intricacies of email urgency prediction. By harnessing cutting-edge techniques, our approach overcomes prevailing limitations in the existing methodologies, offering a pioneering solution for enhanced email management.