GenAI Workforce Evaluation System

A widely used approach in emotional analysis is the BOW model, which is also popular in traditional theme modeling. However, an important limitation to the bow model is that it often considers two contrasting emotional texts as the same due to dependence on individual terms. This results in a change in polarity that the machine learning models struggle to handle effectively. We recommend integrating a semantic analysis program with a relevant dividing line to overcome this challenge to improve accuracy. By taking advantage of a generative AI-based model, we can expand emotions and increase classification. Transformer-based architecture as generic AI models offers advanced abilities in understanding relevant meanings and emotional shades, leading to more accurate emotions and analysis results. Implementation of Generic AI in emotional analysis can revolutionize emotional applications, including the recommended system, customer response evaluation and social media tracking. Applying AI-controlled methods will enable decision-making in different domains and improve user experiences, more accurate in reference-u-extensional emotional classification, reference income-ownable emotion classification.