Enhancing Resume Analysis through Fine-Grained Information Extraction

Abstract

"Current approaches frequently suffer from high computational costs and limited applicability across different domains. While existing Named Entity Recognition (NER) models within resumes provide excellent accuracy when determining the classification of each entity. To overcome these obstacles, research will be done in this paper to identify what model architecture would increase accuracy while lowering resource consumption."