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Development of Bilingual Chatbot for University Related FAQs Using Natural Language Processing and Deep Learning

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Big Data Intelligence and Computing (DataCom 2022)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 13864))

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Abstract

Ever since the rise of the Covid-19 pandemic many organizations have shifted to the new online norm of digitalization. In the list of educational intuitions, the Universities are now offering online programmes to students. The admission process can be frustrating and time-consuming for both the students and the university. Students will have several queries and issues that need to be answered on the spot and clarified before the application process begins. However, chatbots are widely being used everywhere from websites to personal devices. Everyone wants flexibility and ease of access to information faster and in an accurate form, this research paper explores the fundamentals of conversational chatbots in the University system driven by system-chatterbots using neural networks. Focusing on developing a bilingual chatbot that uses Fijian (iTaukei - (Vosa Vakaviti)) and English language through the use of NLP and deep learning algorithms to respond to student FAQs efficiently using intents, a bag of words, and tokenization. This bilingual chatbot can be deployed by any University to provide 24/7 student support to strengthen student communication and ease the flow of information dissemination to its prospective and existing students with prompt responses.

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Correspondence to Rishal Ravikesh Chand or Neeraj Anand Sharma .

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Chand, R.R., Sharma, N.A. (2023). Development of Bilingual Chatbot for University Related FAQs Using Natural Language Processing and Deep Learning. In: Hsu, CH., Xu, M., Cao, H., Baghban, H., Shawkat Ali, A.B.M. (eds) Big Data Intelligence and Computing. DataCom 2022. Lecture Notes in Computer Science, vol 13864. Springer, Singapore. https://doi.org/10.1007/978-981-99-2233-8_6

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  • DOI: https://doi.org/10.1007/978-981-99-2233-8_6

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  • Print ISBN: 978-981-99-2232-1

  • Online ISBN: 978-981-99-2233-8

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