Publication Type : Conference Paper
Publisher : 2017 International Conference on Advances in Computing, Communications and Informatics (ICACCI)
Source : 2017 International Conference on Advances in Computing, Communications and Informatics (ICACCI), IEEE, Udupi, India (2017)
Url : https://ieeexplore.ieee.org/abstract/document/8126079
Keywords : Data mining, Naive Bayes classifier, Text mining
Campus : Amritapuri
School : Department of Computer Science and Engineering, School of Engineering
Department : Computer Science, Sciences
Verified : Yes
Year : 2017
Abstract : Educational Data Mining is a prominent area to explore information in educational fields using data mining algorithms. In this paper we have used few learning algorithms to effectively rate the faculty belonging to an educational institute on the basis of feedback submitted by the students. Our proposed model uses sentimental analysis and machine learning classifier algorithms for capturing the emotions from the students feedback system. This model gives an accurate and efficient way to rate the faculty belonging to a particular educational institute. With this proposed model the faculty will be evaluated and rated with certain specified parameters which will help us to improve the academic and education standard.
Cite this Research Publication : K. S. Krishnaveni, Pai, R. R., and Iyer, V., “Faculty rating system based on student feedbacks using sentimental analysis”, in 2017 International Conference on Advances in Computing, Communications and Informatics (ICACCI), Udupi, India, 2017