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    Domain specific conversational intelligent agents: natural language processing in real world applications

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    Natural language processing (NLP) is the branch of Artificial Intelligence (AI) studies that will shape the future of computing and Human Computer Interaction (HCI). Operational complexity of a conversational intelligent agent (Chat-bot) stems from human-related, linguistic and computational aspects. In this study, we define an architectural description of a chat-bot, address the NLP problems which needs to be solved and provide our proposed solutions for a functional conversational intelligent agent. The importance of Bayesian Statistics and Data mining of domain specific text and expected expansion areas are discussed for future research in the conversational AI development
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