Extension and Prerequisite: An Algorithm to Enable Relations Between Responses in Chatbot Technology
Abbas Saliimi Lokman and Jasni Mohamad Zain
DOI : 10.3844/jcssp.2010.1212.1218
Journal of Computer Science
Volume 6, Issue 10
Problem statement: Artificial intelligence chatbot is a technology that makes interactions between man and machines using natural language possible. From literature, we found out that in general, chatbot are functions like a typical search engine. Although chatbot just produced only one output instead of multiple outputs/results, the basic process flow is the same where each time an input is entered, the new search will be done. Nothing related to previous output. This research is focused on enabling chatbot to become a search engine that can process the next search with the relation to the previous search output. In chatbot context, this functionality will enhance the capability of chatbot’s input processing. Approach: In attempt to augment the traditional mechanism of chatbot processes, we used the relational database model approach to redesign the architecture of chatbot in a whole as well as incorporated the algorithm of Extension and Prerequisite (our proposed algorithm). By using this design, we had developed and tested Virtual Diabetes physician (ViDi), a web-based chatbot that function in specific domain of Diabetes education. Results: Extension and prerequisite enabled relations between responses that significantly make it easier for user to chat with chatbot using the same approach as chatting with an actual human. Chatbot can give different responses from the same input given by user according to current conversation issue. Conclusion: Extension and prerequisite makes chatting with chatbot becomes more likely as chatting with an actual human prior to the relations between responses that produce a response related to the current conversation issue.
© 2010 Abbas Saliimi Lokman and Jasni Mohamad Zain. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.