International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395-0056 Volume: 11 Issue: 05 | May 2024
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p-ISSN: 2395-0072
ADAPTIVE CHATBOTS: ENHANCING USER EXPERIENCE THROUGH INTERACTIVE LEARNING AND DYNAMIC RESPONSE REFINEMENT Abhi Ram Reddy Salammagari*1, Gaurava Srivastava*2 247 Ai Inc., USA Oracle America Inc., USA -----------------------------------------------------------------------***---------------------------------------------------------------------ABSTRACT The rapid advancement of artificial intelligence has propelled chatbots into a new era of interactive learning and adaptation. This article delves into the concepts, mechanisms, and applications of adaptive chatbots that utilize machine learning and natural language processing to constantly improve their responses through user interactions. The potential of these technologies in personalized learning, customer service, and improving the user experience is emphasized by looking at the main parts of adaptive chatbot systems and the learning process that makes dynamic response refinement possible. The article delves into recent advancements in machine learning algorithms, natural language processing, and the rise of self-improving chatbots. In addition, the challenges related to privacy, security, and the complexity of interpreting human language and sentiment in the context of interactive learning and adaptation are addressed. Finally, it is important to highlight the importance of future research and development in finding a balance between automation and human-like interaction in order to fully unlock the potential of AI-driven chatbots. Keywords: Adaptive Chatbots, Interactive Learning, Natural Language Processing, Personalized User Experience, Machine Learning Algorithms
INTRODUCTION The rise of artificial intelligence (AI) has completely transformed the way chatbots engage with users, allowing them to constantly learn and adapt based on user interactions [1]. The interactive learning and adaptation approach has revolutionized chatbots, turning them into intelligent conversational agents that offer personalized and engaging user experiences [2]. Through the use of advanced machine learning algorithms and natural language processing (NLP) techniques, these adaptive chatbots can continuously improve their responses by incorporating user feedback and adapting to changing user requirements [3]. The applications of chatbots are wide-ranging, covering personalized education, customer support, and user experience enhancement [4]. Exploring the concepts, mechanisms, advancements,
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