Next Article in Journal
Automatic Correction of an Automated Guided Vehicle’s Course Using Measurements from a Laser Rangefinder
Previous Article in Journal
Differentiation of the Wright Functions with Respect to Parameters and Other Results
 
 
Article
Peer-Review Record

A Location–Time-Aware Factorization Machine Based on Fuzzy Set Theory for Game Perception

Appl. Sci. 2022, 12(24), 12819; https://doi.org/10.3390/app122412819
by Xiaoxia Xie, Zhenhong Jia *, Hongzhan Shi and Xianxing Zhu
Reviewer 1:
Reviewer 2: Anonymous
Reviewer 4:
Appl. Sci. 2022, 12(24), 12819; https://doi.org/10.3390/app122412819
Submission received: 30 October 2022 / Revised: 11 December 2022 / Accepted: 12 December 2022 / Published: 14 December 2022

Round 1

Reviewer 1 Report

The Paper is nicely written. The paper proposes a location-time-aware factorization machine based on fuzzy set theory to predict the location and time projection of the game users. The topic is relevant to the field as it is important to know the user perception which can significantly enhance the quality of services. Authors have improved the prediction accuracy and focused on interpretability of the prediction. Authors compared the prediction accuracy with other methods and proved that performance of their method is better then most of other existing methods. A pseudocode of the proposed method will benefit the readers. some minor comments: 1. All the abbreviations should be defined when used for the first time in the paper. 2. There are several typo mistakes in the paper. 3. Line 198, page 5, Xnew services is not defined. 4. Line 280, define the evaluation metrics. 5. Page 10, the last three rows are proposed algorithms. So the last row represents what? 6. Since the data is not big. So it is better if the results are presented as five folds cross-validation and table 4 may include the mean and standard deviation of the performance.

Author Response

Please see the attachment

Author Response File: Author Response.docx

Reviewer 2 Report

This paper proposes a location-time-aware factorization machine model (LTFM)  using the location projection, time projection of users and services and fuzzy set theory. 

Overall the paper is interesting and addressing an important research direction. This paper can be improved further. 

Properly introduce the area, why A Location-Time-Aware Factorization? why fuzzy set theory? why these are important for Game Perception? what are the other theories? 

after introduction section, add detailed related work section, in which discuss existing methods, their importance, research gap, advantages and dis-advantages etc. 

equation 3 and equation 4 need futher details and explaination. 

experemntal results and analysis should be a separate and complete section. 

The paper seems incomplete in its current state. organization of the paper is not fine. adding related work section will further improve the References as well. 

i donot know what, but something is missing in the paper, may be properly organizing the paper in proper sections will eliminate the missing factor. 

Author Response

Please see the attachment.

Author Response File: Author Response.docx

Reviewer 3 Report

Please see the attachment.

Comments for author File: Comments.pdf

Author Response

Please see the attachment.

Author Response File: Author Response.docx

Reviewer 4 Report

I recommend the minor revision of this article according to the given below points.

1.       Literature review is very short, include some recent work related to the topic discussed.

2.       Too many short forms are used kindly key in a table for all the short form or abbreviation are used.

3.       Sometimes you used only reference number like [x] and sometimes you used reference number along the author’s name. See the introduction paragraph # 04 and 01 for the clarity. You should put in the same pattern for all the reference.

4.       Some extra spaces are used, for reference see page # 09, line # 289-295. Remove the extra spaces.

5.       All the references are not in the same pattern. You should put into the same pattern in revision.

 

6.       Grammar is quite rough. 

Author Response

Please see the attachment.

Author Response File: Author Response.docx

Round 2

Reviewer 2 Report

none

Author Response

We appreciate your careful reading of our manuscript and your valuable suggestions. We have checked our manuscript with our native English-speaking colleagues and have revised it accordingly. Thank you again for your suggestions.

Reviewer 3 Report

The authors have incorporated the comments successfully and there is no further changes are required from my side. 

However, the authors are advised to check the grammar of the article before final submission as still grammar issues persist in the article.

Author Response

We appreciate your careful reading of our manuscript and your valuable suggestions. We have checked our manuscript with our native English-speaking colleagues and have revised it accordingly. Thank you again for your suggestions.

Back to TopTop