| Title |
EduChat: An AI-Based Chatbot for University-Related Information Using a Hybrid Approach |
| ID_Doc |
67765 |
| Authors |
Dinh, H; Tran, TK |
| Title |
EduChat: An AI-Based Chatbot for University-Related Information Using a Hybrid Approach |
| Year |
2023 |
| Published |
Applied Sciences-Basel, 13, 22 |
| DOI |
10.3390/app132212446 |
| Abstract |
The digital transformation has created an environment that fosters the development of effective chatbots. Through the fusion of artificial intelligence and data, these chatbots have the capability to provide automated services, optimize customer experiences, and reduce workloads for employees. These chatbots can offer 24/7 support, answer questions, perform transactions, and provide rapid information, contributing significantly to the sustainable development processes of businesses and organizations. ChatGPT has already been applied in various fields. However, to ensure that there is a chatbot providing accurate and useful information in a narrow domain, it is necessary to build, train, and fine-tune the model based on specific data. In this paper, we introduce EduChat, a chatbot system for university-related questions. EduChat is an effective artificial intelligence application designed by combining rule-based methods, an innovative improved random forest machine learning approach, and ChatGPT to automatically answer common questions related to universities, academic programs, admission procedures, student life, and other related topics. This chatbot system helps provide quick and easy information to users, thereby reducing the time spent searching for information directly from source documents or contacting support staff. The experiments have yielded positive results. |
| Author Keywords |
engineering; chatbot engineering; AI-based chatbot; EduChat; improved random forest; University Consulting |
| Index Keywords |
Index Keywords |
| Document Type |
Other |
| Open Access |
Open Access |
| Source |
Science Citation Index Expanded (SCI-EXPANDED) |
| EID |
WOS:001120781500001 |
| WoS Category |
Chemistry, Multidisciplinary; Engineering, Multidisciplinary; Materials Science, Multidisciplinary; Physics, Applied |
| Research Area |
Chemistry; Engineering; Materials Science; Physics |
| PDF |
https://www.mdpi.com/2076-3417/13/22/12446/pdf?version=1700226438
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