Designing and Implementing Chatbot Dialogues for Effective Knowledge Exchange: A Methodological Approach

This study delves into integrating external knowledge sources into large language model (LLM) chatbots, thereby establishing a framework for interaction among chatbots equipped with diverse knowledge repositories. The proposed methodological approach aims to thoroughly examine the interaction dynamics produced by these chatbots. Nonetheless, analyzing these interactions entails considerable complexities. The research introduces a groundbreaking evaluation method-ology named Text Representing Centroids (TRC). This technique comprehensively evaluates and quantifies the effectiveness of knowledge transfer and collective conceptualization within the chatbot context. The implementation of TRC in analyzing chatbot dialogues across five distinct datasets produced positive outcomes, highlighting significant relational value. These datasets demonstrated a maximum average distance of 0.986, indicating a robust capacity to capture the fundamental nature and coherence of the dialogues.