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Stream/Area:
-
Subject:
-
Paper ID:
IJSREM37140
Volume:
8 |
8 |
Aug 2024
Pages:
Publication Frequency:
Monthly (12 issues per year)
License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.
Chatbots have become ubiquitous in various domains, ranging from customer service to personal assistants Chatbots have become ubiquitous in various domains, ranging from customer service to personal assistants, owing to their ability to provide instant responses and streamline interactions. Because they can respond quickly and expedite encounters, chatbots have become commonplace in a variety of industries, including customer service and personal assistants. Ensuring a productive and interesting user-chatbot relationship is still a big challenge, though. An all-encompassing strategy to improve user interaction with intelligent chatbots is presented in this research. Natural language understanding (NLU), context awareness, personalised answers, and emotional intelligence are some of the main elements of the method. By utilising cutting-edge machine learning and natural language processing methods, the suggested strategy allows chatbots to grasp user inquiries with precision, deduce context from previous conversations, and customise responses based on personal preferences. Comprehensive user research and performance criteria are used to assess the success of the suggested strategy, which shows promise in providing personalised, emotionally intelligent, and engaging interactions. By using this strategy, businesses may employ chatbots as effective instruments for improving user experience and accomplishing their goals across a range of applications. Moreover, the incorporation of emotional intelligence functionalities enables chatbots to identify and react suitably to user sentiments, consequently cultivating compassionate and significant exchanges.
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Publication Date
8/21/2024
Peer Review Type
Double-Blind Peer Review
Review Rounds: 2
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Conflict of Interest
The authors declare no conflict of interest related to this research work.
Funding Information
No funding information available for this research.
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