Taylor-ChOA: Taylor-Chimp Optimized Random Multimodal Deep Learning-Based Sentiment Classification Model for Course Recommendation

Santosh Kumar Banbhrani, Bo Xu, Hongfei Lin and Dileep Kumar Sajnani
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Santosh Kumar Banbhrani: School of Computer Science and Technology, Dalian University of Technology, Ganjingzi District, Dalian 116024, China
Bo Xu: School of Computer Science and Technology, Dalian University of Technology, Ganjingzi District, Dalian 116024, China
Hongfei Lin: School of Computer Science and Technology, Dalian University of Technology, Ganjingzi District, Dalian 116024, China
Dileep Kumar Sajnani: School of Computer Science and Engineering, Southeast University, Nanjing 210096, China

Mathematics, 2022, vol. 10, issue 9, 1-26

Abstract: Course recommendation is a key for achievement in a student’s academic path. However, it is challenging to appropriately select course content among numerous online education resources, due to the differences in users’ knowledge structures. Therefore, this paper develops a novel sentiment classification approach for recommending the courses using Taylor-chimp Optimization Algorithm enabled Random Multimodal Deep Learning (Taylor ChOA-based RMDL). Here, the proposed Taylor ChOA is newly devised by the combination of the Taylor concept and Chimp Optimization Algorithm (ChOA). Initially, course review is done to find the optimal course, and thereafter feature extraction is performed for extracting the various significant features needed for further processing. Finally, sentiment classification is done using RMDL, which is trained by the proposed optimization algorithm, named ChOA. Thus, the positively reviewed courses are obtained from the classified sentiments for improving the course recommendation procedure. Extensive experiments are conducted using the E-Khool dataset and Coursera course dataset. Empirical results demonstrate that Taylor ChOA-based RMDL model significantly outperforms state-of-the-art methods for course recommendation tasks.

Keywords: chimp optimization algorithm; course recommendation; E-learning; long short-term memory; random multimodal deep learning; sentiment classification (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2022
References: View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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