Building Intelligent Chatbot Systems using Meta-Analysis and Deep Learning

Kyldo Jsowd

No s9bza, OSF Preprints from Center for Open Science

Abstract: Chatbot systems have gained significant attention in recent years due to their potential to automate customer interactions and provide personalized assistance. This article presents a novel approach for building intelligent chatbot systems by leveraging the power of meta-analysis and deep learning techniques. In this study, we propose a framework that combines meta-analysis, which synthesizes findings from existing chatbot research, with deep learning algorithms to enhance the performance and intelligence of chatbot systems. We explore the application of deep learning models, such as recurrent neural networks (RNNs) and transformer models, for various chatbot tasks, including natural language understanding, dialogue management, and response generation

Date: 2023-07-16
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Persistent link: https://EconPapers.repec.org/RePEc:osf:osfxxx:s9bza

DOI: 10.31219/osf.io/s9bza

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