A Chatbot Intent Classifier for Supporting High School Students

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dc.contributor.authorK. Assayed, Suha
dc.contributor.authorShaalan, Khaled
dc.contributor.authorAlkhatib, Manar
dc.date.accessioned2025-05-14T09:19:40Z
dc.date.available2025-05-14T09:19:40Z
dc.date.issued2022
dc.description.abstractINTRODUCTION: An intent classification is a challenged task in Natural Language Processing (NLP) as we are asking the machine to understand our language by categorizing the users’ requests. As a result, the intent classification plays an essential role in having a chatbot conversation that understand students’ requests. OBJECTIVES: In this study, we developed a novel chatbot called “HSchatbot” for predicting the intent classifications from high school students’ enquiries. Evidently, students in high schools are the most concerned among all students about their future; thus, in this stage they need an instant support in order to prepare them to take the right decision for their career choice. METHODS: The authors in this study used the Multinomial Naive-Bayes and Random Forest classifiers for predicting the students’ enquiries, which in turn improved the performance of the classifiers by using the feature’s extractions. RESULTS: The results show that the random forest classifier performed better than Multinomial Naive-Bayes since the performance of this model is checked by using different metrics like accuracy, precision, recall and F1 score. Moreover, all showed high accuracy scores exceeding 90% in all metrics. However, the accuracy of Multinomial Naive-Bayes classifier performed much better when using CountVectorizers compared to using the TF-IDF. CONCLUSION: In the future work, the results will be analysed and investigated in order to figure out the main factors that affect the performance of Multinomial Naive-Bayes classifier, as well as evaluating the model with using a large corpus of students’ questions and enquiries.
dc.identifier.urihttps://bspace.buid.ac.ae/handle/1234/3009
dc.language.isoen
dc.titleA Chatbot Intent Classifier for Supporting High School Students
dc.typeArticle
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Professor Khaled Shaalan