Urban Expressway Renewal Strategy Based on Knowledge Graphs

Round 1

Reviewer 1 Report

General comments

As an important element of urban infrastructure renewal, urban expressway renewal is of great significance to improve the commuting efficiency of cities (especially metropolitan cities), strengthen the service capacity of urban road facilities, and enhance the quality of cities. Aiming at the advantages of knowledge graph in the integration of multi-source data and assisted decision making based on knowledge reasoning, this paper provides assisted decision support for urban expressway renewal with the help of knowledge graph. In this paper, firstly, we sort out the concepts related to road renewal from road maintenance standards, design ontology concept fuzzy matching algorithm to extract relevant concepts in existing ontologies, construct concept models, and build the knowledge graph of expressway renewal with ontology as the carrier. Then, based on road maintenance guidelines and road attributes, this paper proposes a knowledge reasoning rule combined with case similarity for expressway renewal strategy. The final experimental results verify the feasibility of this paper's expressway renewal strategy based on knowledge graph.

In general, this paper is well posed, interesting and clearly presented. I believe it makes a valuable contribution in Urban expressway renewal strategy.

Final decision:

The paper is accepted for publication after minor revision

- Please, clarify which one of the assumptions is new in this area in the problem definition.

- Please, check the grammar of the paper.

- author should update the introduction section to include the novel literatures to make the paper more convenient. I do not propose you any especial reference due to ethical issues.

 

1-The Karush–Kuhn–Tucker (KKT) optimality conditions for fuzzy-valued fractional optimization problems, 2- A modified TOPSIS approach for solving stochastic fuzzy multi-level multi-objective fractional decision-making problem, 3- A novel interactive approach for solving uncertain bi-level multi-objective supply chain model, 4- Using Interval Operations in the Hungarian Method to Solve the Fuzzy Assignment Problem and Its Application in the Rehabilitation Problem of Valuable Buildings in Egypt. 5- A novel Approach for Fully Intuitionistic Fuzzy Multi-Objective Fractional Transportation Problem., 6- A novel algorithm for generating Pareto frontier of bi-level multi-objective rough nonlinear programming problem.

Author Response

Dear Reviewer, 
Thank you for your kind considerations and comments on our manuscript entitled “Urban expressway renewal strategy based on knowledge graph” (Manuscript ID: applsci-2305646). It is quite helpful for improving the quality of our paper and we have studied comments carefully and have made revision and explanation according to your comments. Please see the attachment.

Best regards, 
Min Zhu
Wenbo Zhou
Tengfei Yuan 
HU-UTS SILC Business School, Shanghai University, 
Shanghai 201800, China 
E-mail address: [email protected]

Author Response File: Author Response.pdf

Reviewer 2 Report

Figure 6.

 knowledge graph example contains mostly only hierarchical relationships «Subclassof». It seems to be more interesting if we give an example with functional relationships and the attributes of these relationships.

 

 

p 164

I don't see what the abbreviation SWRL means. It needs to be expanded

 

Table 5.

if the rule R1 is not the only rule for matching potential risks of expressways, then it is better to name the table – “Example of rules for matching potential risks of expressways”

 It seems to me that in Algorithm 1, Algorithm 2, comments are required that will clarify the meaning of the steps of the algorithm

 

 What is meant by a knowledge graph in this article - could you give a mathematical definition in the form KG = <A,B,C,D,…> - where A is…., B is….?

It seems to me that the suggested approach to case comparison is similar to case based reasoning (CBR). I would encourage the authors to review the studies on CBR in the future. Maybe there is research on this topic based  on CBR .

 

Author Response

Dear Reviewer, 
Thank you for your kind consideration and comments on our manuscript entitled “Urban expressway renewal strategy based on knowledge graph” (Manuscript ID: applsci-2305646). It is quite helpful for improving the quality of our paper and we have studied the comments carefully and have made revisions and explanations according to your comments. Please see the attachment.

Best regards, 
Min Zhu
Wenbo Zhou
Tengfei Yuan 
HU-UTS SILC Business School, Shanghai University, 
Shanghai 201800, China 
E-mail address: [email protected]

Author Response File: Author Response.pdf

Reviewer 3 Report

Some Recommendations to the paper:

1. The organization of the paper should be given in the last paragraph of Introduction section.

2. Keywords should be abbreviated and arranged alphabetically.

3. The authors need to improve the quality of Figure 1 and resize it according to the dimensions of the manuscript.

4.  The authors need to resize the Figure 6 and all tables according to the dimensions of the manuscript.

5. The English language of the manuscript needs to be improved. The authors need to remove the syntactical errors made in the text.

6. Authors need to provide more detailed explanations for the algorithm 1, presented in the sentence

“Specifically, this paper uses owlready2 and concept fuzzy matching strategy (Algorithm 1) to extract reusable concepts and their hierarchical relationships from ENVO and SIO through the identified keywords.”

Is there a literature reference for the algorithm 1 and why it is called fuzzy algorithm? Is the algorithm related to fuzzy logic?

Author Response

Dear Reviewer, 
Thank you for your kind consideration and comments on our manuscript entitled “Urban expressway renewal strategy based on knowledge graph” (Manuscript ID: applsci-2305646). It is quite helpful for improving the quality of our paper and we have studied the comments carefully and have made revisions and explanations according to your comments. Please see the attachment.

Best regards, 
Min Zhu
Wenbo Zhou
Tengfei Yuan 
HU-UTS SILC Business School, Shanghai University, 
Shanghai 201800, China 
E-mail address: [email protected]

Author Response File: Author Response.pdf