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Maximizing Chatbot Performance: Harnessing Meta-Analysis for Enhanced Integration

EasyChair Preprint no. 12752

8 pagesDate: March 27, 2024


Chatbot systems have become integral in various domains, yet their performance often fluctuates due to diverse user needs and evolving contexts. In this study, we propose a novel approach to maximize chatbot performance through the integration of meta-analysis techniques. By systematically analyzing a wide array of existing studies and data sources, we identify key factors influencing chatbot efficacy and develop a comprehensive framework for enhanced integration. Our approach leverages meta-analysis to synthesize findings, uncover patterns, and derive actionable insights for optimizing chatbot design and functionality. Through this method, we aim to address the inherent challenges of chatbot performance variability and empower developers to create more robust and adaptive conversational agents.

Keyphrases: Artificial Intelligence, Chatbots, conversational agents, Integration, meta-analysis, Natural Language Processing, performance optimization, user experience

BibTeX entry
BibTeX does not have the right entry for preprints. This is a hack for producing the correct reference:
  author = {Lia Don},
  title = {Maximizing Chatbot Performance: Harnessing Meta-Analysis for Enhanced  Integration},
  howpublished = {EasyChair Preprint no. 12752},

  year = {EasyChair, 2024}}
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