Novel Taxonomy for E-learning Recommender System Using Opinion Mining-Reference-Cited by-同舟云学术

Novel Taxonomy for E-learning Recommender System Using Opinion Mining

Published:2023 Issue: Volume: Page:374-385
ISSN:1865-0929
Container-title:Communications in Computer and Information Science
language:
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Author:

Kalpana ^ORCID,Chauhan Shardul Singh^ORCID,Singh Mahesh Kumar^ORCID,Bagoria Renu^ORCID

Publisher

Springer Nature Switzerland

Link

https://link.springer.com/content/pdf/10.1007/978-3-031-35644-5_30

Reference26 articles.

1. Zhang, Q., Lu, J., Zhang, G.: Recommender systems in E-learning. J. Smart. Environ. Green. Comput. 1, 76–89 (2021). https://doi.org/10.20517/jsegc.2020.06

2. Kurt, A.A., Emiroglu, B.G.: Analysis of students’ online information searching strategies, exposure to internet information pollution and cognitive absorption levels based on various variables. Malays. Online J. Educ. Technol. 6(1), 18–29 (2018)

3. Saleh, M.A., Palaniappan, S., Abdalla, N.A.A.: Education is an overview of data mining and the ability to predict the performance of students. Edukasi 15(1), 19–28 (2021). https://journal.unnes.ac.id/nju/index.php/edukasi,

4. Ahmed, A.M., Rizaner, A., Ulusoy, A.H.: Using data mining to predict instructor performance. Procedia Comput. Sci. 102, 137–142 (2016)

5. Angeli, C., Howard, S.K., Ma, J., Yang, J., Kirschner, P.A.: Data mining in educational technology classroom research: can it make a contribution? Comput. Educ. 113, 226–242 (2017)

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