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Automated information retrieval and services of graduate school using chatbot system
International Journal of Electrical and Computer Engineering ; 12(5):5330-5338, 2022.
Article in English | Scopus | ID: covidwho-1988500
ABSTRACT
Automated information retrieval and servicing systems are a priority demand system in today's businesses to ensure instantaneous customer satisfaction. The chatbot system is an incredible technological application that enables communication channels to automatically respond to end-users in real-time and 24 hours a day. By providing effective services for retrieving information and electronic documents continuously and automating the information service system, the coronavirus disease (COVID-19) is challenging to promote graduate school programs, update news, and retrieve student information in this era. This article discusses automated information retrieval and services based on the architecture, components, technology, and experiment of chatbots. The chatbot system's primary functions are to deliver the course and contact information, answer frequency questions, and provide a link menu to apply for our online course platform. We manage the entire functional process of gathering course information and submitting an application for a course online. The final results compare end users' perceptions of chatbot system usage to onsite services to ensure that the chatbot system can be integrated into the university's information system, supporting university-related questions and answers. We may expand our chatbot system's connection to the university's server to provide information services to students in various informative areas for future research. © 2022 Institute of Advanced Engineering and Science. All rights reserved.
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Full text: Available Collection: Databases of international organizations Database: Scopus Language: English Journal: International Journal of Electrical and Computer Engineering Year: 2022 Document Type: Article

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Full text: Available Collection: Databases of international organizations Database: Scopus Language: English Journal: International Journal of Electrical and Computer Engineering Year: 2022 Document Type: Article