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Extending a Conventional Chatbot Knowledge Base to External Knowledge Source and Introducing User-Based Sessions for Diabetes Education

Extending a Conventional Chatbot Knowledge Base to External Knowledge Source and Introducing User-Based Sessions for Diabetes Education
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Author(s): Shafquat Hussain (Western Sydney University, Australia) and Athula Ginige (Western Sydney University, Australia)
Copyright: 2019
Pages: 11
Source title: Enabling Technologies and Architectures for Next-Generation Networking Capabilities
Source Author(s)/Editor(s): Mahmoud Elkhodr (Central Queensland University, Australia)
DOI: 10.4018/978-1-5225-6023-4.ch015

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Abstract

Chatbots or conversational agents are computer programs that interact with users using natural language through artificial intelligence in a way that the user thinks he is having dialogue with a human. One of the main limits of chatbot technology is associated with the construction of its local knowledge base. A conventional chatbot knowledge base is typically hand constructed, which is a very time-consuming process and may take years to train a chatbot in a particular field of expertise. This chapter extends the knowledge base of a conventional chatbot beyond its local knowledge base to external knowledge source Wikipedia. This has been achieved by using Media Wiki API to retrieve information from Wikipedia when the chatbot's local knowledge base does not contain the answer to a user query. To make the conversation with the chatbot more meaningful with regards to the user's previous chat sessions, a user-specific session ability has been added to the chatbot architecture. An open source AIML web-based chatbot has been modified and programmed for use in the health informatics domain. The chatbot has been named VDMS – Virtual Diabetes Management System. It is intended to be used by the general community and diabetic patients for diabetes education and management.

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