Adaptive Chatbots: Real-Time Sentiment Analysis for Customer Support

Rekha Sivakolundhu, Deepak Nanuru Yagamurthy
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Abstract

In the era of digital transformation and increasing online interactions, customer support is a critical aspect of business success. This paper investigates the development of adaptive customer support chatbots that use real-time sentiment analysis to generate contextually appropriate responses. By leveraging advanced sentiment detection techniques, the system aims to enhance user interaction, satisfaction, and overall customer service experience. This innovation is particularly relevant in today's fast-paced, digitally connected world where personalized and empathetic customer service can significantly impact brand loyalty and customer retention. The proposed approach addresses the growing demand for more intelligent and emotionally aware chatbots, aligning with current trends in artificial intelligence and consumer expectations.
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自适应聊天机器人:客户支持的实时情感分析
在数字化转型和在线互动日益增加的时代,客户支持是企业成功的一个重要方面。本文研究了自适应客户支持聊天机器人的开发,该聊天机器人利用实时情感分析生成与上下文相适应的回复。通过利用先进的情感检测技术,该系统旨在增强用户互动、满意度和整体客户服务体验。在当今快节奏的数字互联世界中,个性化和感同身受的客户服务会极大地影响品牌忠诚度和客户保留率,因此这种创新尤为重要。所提出的方法满足了人们对更智能、更具情感意识的聊天机器人日益增长的需求,符合当前人工智能的发展趋势和消费者的期望。
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