Conversational AI: A Comprehensive Study of Chatbot Development with Emphasis on Implementation on User Experience
Keywords:
Chatbot, Dialog Flow, Conversational AIAbstract
Chatbots and conversational technologies have turned into a popular study topic, and many firms are beginning to use them to fulfil simple communication roles. Business organizations may rapidly and easily design their own systems using a wide range of accessible frameworks for chat-bot development from software behemoths. However, these platforms frequently lack a comprehensive set of tools for creating a controllable, flexible, and robust chatbot.As a result, extra machine learning mechanisms are typically required to boost performance. In this research, we show how a chatbot system can respond to frequently asked questions (FAQs) from our institution's website using machine learning. To deal with extensive and sophisticated user questions, the system incorporates several forms of user inquiries as well as a vector similarity analysis component. Furthermore, Google's Dialog Flow framework 1 is employed for the purpose of identification.
References
Shawar BA, Atwell E. Different measurement metrics to evaluate a chatbot system. In Proceedings of the workshop on bridging the gap: Academic and industrial research in dialog technologies2007; pp. 89-96. [Google Scholar]
Braun D, Mendez AH, Matthes F, et al. Evaluating natural language understanding services for conversational question answering systems. In Proceedings of the 18th annual SIGdial meeting on discourse and dialogue 2017; pp. 174-185. [Google Scholar]
Kuligowska K. Commercial chatbot: performance evaluation, usability metrics and quality standards of embodied conversational agents. Professionals Center for Business Research2015; 2. [Google Scholar]
Quarteroni S, Manandhar S. A chatbot-based interactive question answering system. Decalog 2007; 83. [Google Scholar]
Yan Z, Duan N, Bao J, et al. Docchat: An information retrieval approach for chatbot engines using unstructured documents. In Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics 2016; 1: 516-25. [Google Scholar
