Paper Title
SENTIMENTAL ANALYSIS FOR REAL TIME FEEDBACK USING ML ALGORITHMS
Article Identifiers
: Keywords
Feedback system, SVM algorithm, Machine learning, Naive Bayes.
Abstract
In The research was conducted in order to present the student feedback system analysis model for improving the quality of teaching in academic institutions and universities. The system primarily utilizes a machine learning algorithm and textual feedback. This system has been configured to analyze student feedback in the form of comments, opinions, and reviews about teachers' performance. The textual feedback offers valuable insights into overall teaching quality and suggests valuable ways to improve teaching methodology. The purpose of this research is to look into various machine learning approaches and determine their importance. SVM, Random Forest, Nave Bayes algorithm, and lexical analysis are examples of machine learning techniques. SVM has the highest accuracy but requires more time to train for large datasets and is used for regression and classification to classify text. The collection contains data on the effectiveness of instruction and learning. This project looks at the textual comments in the text document to classify student feedback into positive, negative, and neutral categories. The system assists in reducing manual work by collecting feedback and storing it in a database accessible to authorized individuals. The teacher receives feedback analysis in the form of ratings and graphs, making data visualization easier. This system is an effective method for providing teachers with qualitative feedback that improves students' learning.
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How To Cite (APA)
N.VYSHNAVI, DR.A.PARIVAZHAGAN, P.RANGA VIKAS, K.CHARISHMA MADHAVI, & S.GOVINDA RAO (November-2023). SENTIMENTAL ANALYSIS FOR REAL TIME FEEDBACK USING ML ALGORITHMS. INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT, 8(11), b237-b241. https://ijnrd.org/papers/IJNRD2311131.pdf
Issue
Volume 8 Issue 11, November-2023
Pages : b237-b241
Other Publication Details
Paper Reg. ID: IJNRD_208448
Published Paper Id: IJNRD2311131
Downloads: 000122018
Research Area: Engineering
Author Type: Indian Author
Country: virudhnagar, tamilnadu, India
Published Paper PDF: https://ijnrd.org/papers/IJNRD2311131.pdf
Published Paper URL: https://ijnrd.org/viewpaperforall?paper=IJNRD2311131
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