DOIONLINE 
DOIONLINE Publish In |
International Journal of Advance Computational Engineering and Networking (IJACEN)-IJACEN |
 Journal Home Volume Issue |
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Issue |
Volume-7, Issue-9 ( Sep, 2019 ) | |||||||||
Paper Title |
Intelligent AI based Dialogue Agent to Enhance Communication in Organ Transplant Networks | |||||||||
Author Name |
Sumalatha.M.R, Aravind Rajagopalan, Kaaviya Peranandam, Vishwa S.S.K.M | |||||||||
Affilition |
Professor, Department of Information Technology, MIT Campus, Anna University, Chennai, India B.Tech IV Year, Department of Information Technology, MIT Campus, Anna University, Chennai, India | |||||||||
Pages |
1-6 | |||||||||
Abstract |
Organ Transplantation has become a successful mechanism to cure many chronic diseases which otherwise would have been fatal for the patient‟s life. But, organ transplantation process involves many communication deficiencies that hinder the smooth transplantation process. The process of automation of communication involves adjoining of various hard concepts of Natural language Processing (NLP), Natural Language Understanding (NLU) and Natural Language Generation (NLG). This work proposes an Artificial Intelligence dialogue agent or a Chatbot that can swiftly and accurately manage the communication issues of organ transplantation process by automating the process of providing answers to user‟s queries, where nature of query can be regarding to authorized transplant centers, legal matters concerning transplantation, general information about transplantation, contact points or Non Governmental organizations working in this domain etc. The dialogue agent functions at two major levels. First level has a trained Long Short Term Memory neural Network to generate answers to user‟s queries and the second level performs by displaying best matched sentences from the scraped contents from web that best satisfies the user‟s queries. The results from the experiments proved that the proposed dialog agent was capable of providing accurate and precise answers to user‟s questions, thereby proving to be an effective communication enhancement agent in organ transplant networks. Keywords - AI, NLP, NLG, Dialogue agent, Organ Transplantation, Chatbot, LSTM, Glove Encoding. | |||||||||
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