multinomial Naïve Bayes
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Machine Learning Based Sentiment Analysis of Student Feedback in Higher Education
Abstract: Educational institutions routinely collect feedback from students to understand their perceptions of academic programs, infrastructure, and campus facilities, to improve the overall quality of the college environment. In current practice, feedback is often gathered using numerical or grade-based rating systems, which tend to oversimplify student opinions and may overlook important details related to their level of satisfaction. In contrast, open-ended textual feedback allows students to clearly express their views, concerns, …
Published in International Journal of Data Structure Studies · Vol. 4, Issue 1, 2026 · pp. 01–10 Read article
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Detection of Phishing Website URLs and Email/SMS Using Random Forest and Multinomial Naive Bayes
Abstract: Currently, phishing attacks via SMS/email and URL have become significant threat to cybersecurity, posing risks to both individuals and organizations alike. Phishing attacks typically involve the creation of fraudulent websites or the dissemination of deceptive emails and SMS messages to trick users into disclosing sensitive information such as passwords, credit card numbers or personal details. To respond to these attacks, we develop a robust system for the detection of phishing …
Published in Journal of Computer Technology & Applications · Vol. 16, Issue 1, 2025 · pp. 22–30 Read article