Research on Real-Time User Feedback Acceleration Mechanism Based on Genai Chatbot

Abstract

As GenAI adoption continues to surge, AI chatbots have become one of the most prominent and widely deployed applications of artificial intelligence, especially across sectors such as customer service, education, healthcare assistance, and content generation. In these domains, the real-time feedback loop generated through user interactions-and the system's ability to adapt based on this feedback-plays a critical role in determining the quality, reliability, and intelligence level of chatbot responses. As user expectations for accuracy, immediacy, and personalization continue to rise, the demand for a more robust and efficient feedback mechanism has become increasingly urgent. However, existing GenAI chatbot systems often struggle to maintain sufficient speed and stability in their real-time feedback loops. Problems such as delayed feedback processing, insufficiently refined semantic interpretation, and occasional inaccuracies in generated responses weaken the system's overall performance and may negatively affect user experience. These challenges highlight the necessity of integrating real-time feedback more directly and effectively into the core model processing pipeline. This article aims to address the above limitations by investigating how real-time user feedback can be seamlessly incorporated into AI model interactions to enhance response efficiency and accuracy. The research proposes an integrated optimization strategy that includes streamlining data transmission paths, improving semantic parsing algorithms, refining intent recognition processes, and applying targeted model fine-tuning methods. These enhancements work together to accelerate the system's feedback processing capabilities and strengthen its adaptive response mechanism. Through extensive experimental testing and comparative analysis, the study demonstrates that the optimized system significantly improves the efficiency of the feedback loop, enhances the coherence and precision of generated responses, and ultimately boosts user satisfaction. The findings suggest that the integration of real-time feedback into GenAI model processing offers a viable pathway for building more intelligent, adaptive, and user-centered chatbot systems suitable for broader practical deployment.