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Digital Object Identifier (DOI) : 10.14569/IJACSA.2017.080930
Article Published in International Journal of Advanced Computer Science and Applications(IJACSA), Volume 8 Issue 9, 2017.
Abstract: Chatbots or chatter bots have been a good way to entertain one. This paper emphasizes on the use of a chatbot in the diagnosis of Achluophobia – the fear of darkness and autism disorder. Autism and Achluophobia (fear of darkness) are the most common neurodevelopment disorders usually found in children. State of the art trivial diagnosis methods require a lot of time and are also unable to maintain the case history of psychological disease. A chatbot has been developed in this work which can diagnose the severity of disease based on user’s text based questions. It performs Natural Language Processing (NLP) for meaning extraction and uses Decision Trees to characterize a patient in terms of possible disease. NLP unit extracts meaning of keywords defining intensity of disease’s symptoms, from user’s chat. After that similarity matching of sentence containing keywords is performed. Depth First Search (DFS) technique is used for traversing Decision Tree and making decision about severity of disease. The proposed system namely Aquabot, proves to be an efficient technique in diagnosing Achluophobia and Autism. Aquabot is useful for practitioner psychologists to assist a human psychologist. Aquabot not only saved time and resources but also achieved an accuracy of 88 percent when compared against human psychologist’s diagnosed results.
Sana Mujeeb, Muhammad Hafeez Javed and Tayyaba Arshad, “Aquabot: A Diagnostic Chatbot for Achluophobia and Autism ” International Journal of Advanced Computer Science and Applications(IJACSA), 8(9), 2017. http://dx.doi.org/10.14569/IJACSA.2017.080930