Review History


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Summary

  • The initial submission of this article was received on April 13th, 2023 and was peer-reviewed by 3 reviewers and the Academic Editor.
  • The Academic Editor made their initial decision on May 2nd, 2023.
  • The first revision was submitted on May 12th, 2023 and was reviewed by 2 reviewers and the Academic Editor.
  • The article was Accepted by the Academic Editor on May 15th, 2023.

Version 0.2 (accepted)

· May 15, 2023 · Academic Editor

Accept

Dear authors,

Thank you for clearly addressing all of the reviewers' comments. Your article is accepted for publication now.

Best wishes,

[# PeerJ Staff Note - this decision was reviewed and approved by Jyotismita Chaki, a PeerJ Computer Science Section Editor covering this Section #]

Reviewer 2 ·

Basic reporting

I am satisfied with the improvements, so no more comments. Please go ahead and Good luck

Experimental design

I am satisfied with the improvements, so no more comments. Please go ahead and Good luck

Validity of the findings

I am satisfied with the improvements, so no more comments. Please go ahead and Good luck

Additional comments

I am satisfied with the improvements, so no more comments. Please go ahead and Good luck

Reviewer 3 ·

Basic reporting

My suggestions are addressed, therefore I am satisfied with the current version of the paper for further process

Experimental design

My suggestions are addressed, therefore I am satisfied with the current version of the paper for further process

Validity of the findings

My suggestions are addressed, therefore I am satisfied with the current version of the paper for further process

Additional comments

No more comments

Version 0.1 (original submission)

· May 2, 2023 · Academic Editor

Major Revisions

Dear authors,

Your article has not been recommended for publication in its current form. However, we do encourage you to address the concerns and criticisms of the reviewers and resubmit your article once you have updated it accordingly.

Best wishes,

[# PeerJ Staff Note: Please ensure that all review comments are addressed in a rebuttal letter and any edits or clarifications mentioned in the letter are also inserted into the revised manuscript where appropriate. It is a common mistake to address reviewer questions in the rebuttal letter but not in the revised manuscript. If a reviewer raised a question then your readers will probably have the same question so you should ensure that the manuscript can stand alone without the rebuttal letter. Directions on how to prepare a rebuttal letter can be found at: https://peerj.com/benefits/academic-rebuttal-letters/ #]

Reviewer 1 ·

Basic reporting

I reviewed your work titled "An Artificial Intelligence-based news feature mining system based on the Internet of Things and Multisensor Fusion" in detail. I would like to point out that the work is generally well-written. However, there are some points that I see missing in the study. I believe that if these deficiencies are corrected, the quality of the work will increase.

Experimental design

In the study, Iot-based hardware technology and AI technology were used together. A high accuracy value of around 98% was obtained in the proposed model. Limitations of the study should be addressed and information should be given about future studies. The hardware part of the study is detailed, but the software side is detailed. It should be presented which artificial intelligence model is used in the study. In addition, information about the data set should be given.

Validity of the findings

The figures used in the study remained very plain and simple, updating the relevant figures will increase the design quality of the article. The conclusion section should be detailed and the results of the study should be included.

Additional comments

Finally, spelling errors in the study were reviewed.

Reviewer 2 ·

Basic reporting

this paper proposes a news data transmission feature and mining system. Based on the Internet of Things technology, the data collector, data analyzer, central controller and sensor are designed in the hardware area. The performance of each device is the highest configuration, so as to realize the function call of the system software area. This study can give correct news orientation and improve the efficiency of news communication in the process of formulating the news communication mode. Although the results of this paper have excellent value, there are also some problems, some revisions needed to be revised to make sure that the manuscript can be accepted. The commonly problems are as follows:
1. Check target journal/ institution for prescribed format.
2. Moreover, double-check spelling, punctuation marks, and titles for accuracy in copying the texts verbatim.
3. Please note that acronyms of terms used just once in the abstract need not be included.
4. Instead, the acronyms can be introduced in the main text, where they are repeatedly mentioned.
5. There is no clear explanation for GJ-HD, DCNF, etc. in the abstract.
6. The author implants network operation protocol based on artificial intelligence algorithm in the system software area to improve the system's processing efficiency of news data. The specific algorithm used should be clearly expressed to avoid some vague explanations;
7. The title Software design of Section 3 needs to be replaced, and the title selection should be more consistent with the introduced content;
8. What is the Artificial intelligence technology used? Again, this needs to be explained rationally;
9. It is worth noting that there are three forms of text, picture and video in the data set, and the fusion of multimodal data seems to have been neglected.

Experimental design

See above

Validity of the findings

See above

Additional comments

see above comments

Reviewer 3 ·

Basic reporting

In this paper, the Internet of Things and artificial intelligence technology are combined to design a news data transmission characteristics and mining system, and the hardware and software of the system are optimized. The network transmission protocol of artificial intelligence algorithm is implanted in the system software, and the transmission feature model is constructed to realize the fast and accurate mining of news data transmission features. The experimental results show that the accuracy of the system mining news data features is higher than 98%, which can realize efficient news data processing and effectively improve the efficiency of news transmission. My suggestion is to accept it after modification. The following are specific suggestions for modification

 It seems that the collection of news data does not entirely depend on the Internet of Things devices. I doubt the feasibility of this experimental scheme;
 Add more references to Section 2.1, which involves too many difficult terms;
 It is suggested that more formulas should be added in the manuscript for concrete description, otherwise readers cannot have a deeper understanding of this work;
 The result analysis should be based on the data presented, so please add more data descriptions;
 The description of Figure 1 needs to be more detailed, and the connection between each operation module needs to be explained;
 The experiments are very limited and did not conduct the idea;
 The potential contribution of this work to practitioners and the journalism/computer science field is not reflected in the conclusion;
 Number of references is very less, so I will suggest authors add more related and recent references in the list and in the text;
 It will be better to add some references from good journal papers.

Experimental design

In this paper, the Internet of Things and artificial intelligence technology are combined to design a news data transmission characteristics and mining system, and the hardware and software of the system are optimized. The network transmission protocol of artificial intelligence algorithm is implanted in the system software, and the transmission feature model is constructed to realize the fast and accurate mining of news data transmission features. The experimental results show that the accuracy of the system mining news data features is higher than 98%, which can realize efficient news data processing and effectively improve the efficiency of news transmission. My suggestion is to accept it after modification. The following are specific suggestions for modification

 It seems that the collection of news data does not entirely depend on the Internet of Things devices. I doubt the feasibility of this experimental scheme;
 Add more references to Section 2.1, which involves too many difficult terms;
 It is suggested that more formulas should be added in the manuscript for concrete description, otherwise readers cannot have a deeper understanding of this work;
 The result analysis should be based on the data presented, so please add more data descriptions;
 The description of Figure 1 needs to be more detailed, and the connection between each operation module needs to be explained;
 The experiments are very limited and did not conduct the idea;
 The potential contribution of this work to practitioners and the journalism/computer science field is not reflected in the conclusion;
 Number of references is very less, so I will suggest authors add more related and recent references in the list and in the text;
 It will be better to add some references from good journal papers.

Validity of the findings

In this paper, the Internet of Things and artificial intelligence technology are combined to design a news data transmission characteristics and mining system, and the hardware and software of the system are optimized. The network transmission protocol of artificial intelligence algorithm is implanted in the system software, and the transmission feature model is constructed to realize the fast and accurate mining of news data transmission features. The experimental results show that the accuracy of the system mining news data features is higher than 98%, which can realize efficient news data processing and effectively improve the efficiency of news transmission. My suggestion is to accept it after modification. The following are specific suggestions for modification

 It seems that the collection of news data does not entirely depend on the Internet of Things devices. I doubt the feasibility of this experimental scheme;
 Add more references to Section 2.1, which involves too many difficult terms;
 It is suggested that more formulas should be added in the manuscript for concrete description, otherwise readers cannot have a deeper understanding of this work;
 The result analysis should be based on the data presented, so please add more data descriptions;
 The description of Figure 1 needs to be more detailed, and the connection between each operation module needs to be explained;
 The experiments are very limited and did not conduct the idea;
 The potential contribution of this work to practitioners and the journalism/computer science field is not reflected in the conclusion;
 Number of references is very less, so I will suggest authors add more related and recent references in the list and in the text;
 It will be better to add some references from good journal papers.

Additional comments

See above sections

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