HANDLING OF STUDENT FEEDBACK BASED ON TEXT CLASSIFICATION

Abstract

Ensuring quality training has been receiving a lot of attention from university training establishments. Learners play an important role in quality assurance in training and education. To understand the meaning of student feedback on training activities at Nha Trang University (NTU) and to improve the university’s training, we propose to handle student feedback through automatic feedback classification and labeling. The classification and prediction of labels are based on the Support Vector Machine (SVM) and Naive Bayes Classifier (NBC) methods. Experiments with the SVM and NBC methods show positive results, 92.13% and 90.10%, respectively, for the data set of student reviews at Nha Trang University.

Keywords

• naive bayesian classification (nbc)
• phân loại văn bản
• support vector machine (svm)
• ý kiến người học.