State-of-the-Art Survey on Deep Learning-Based Recommender Systems for E-Learning

Round 1

Reviewer 1 Report

The topic is quite interesting but it is more literature-based research rather than scientific. I do not feel this paper is qualified for a scientific community. If the authors produce some realistic GUI, its algorithm, applications, modeling, and quantitative and qualitative analysis then it would be interesting for research publication. Whereas, this research is quite good for a reader to understand the conceptual framework of machine learning techniques, but yet it lacks machine learning methodology, testing, and validation of the dataset. 

Author Response

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Author Response File: Author Response.docx

Reviewer 2 Report

It is seen that a serious effort has been spent by the authors. It is a successful review study on recommender systems. I would like you to consider the following suggestions to contribute to the study:

1)The Abstract section should contain more concrete information about the study.

2) What makes the work innovative? What gap does it fill in the literature? It should be clearly explained.

3) How were the articles examined in this study selected?

4) Figure 2 is not clear. Should it be rebuilt?

5) In the Conclusions Section, clear and concrete information should be given. Figure and table explanations should be given in the Discussion section. In addition, the Conclusion Section should be inclusive of the study. It must be rebuilt.

Author Response

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Author Response File: Author Response.docx

Reviewer 3 Report

This survey article explores the area of recommendation systems that specialized for e-learning. Overall, the area is thoroughly analyzed and the list of reference is extensive. Perhaps, should I need to point out some improvements, these would regard the second section that could be more comprehensive and more referenced.

Author Response

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Author Response File: Author Response.docx

Round 2

Reviewer 1 Report

The paper is now improved. The author has addressed almost all the previous concerns/suggestions. Yet I would suggest adding the author's methodology in a separate section or paragraph or adding an algorithm.

This paper is accepted on current form

Reviewer 2 Report

The requested corrections have been made. I think it's acceptable.