PONE-D-22-03021Goal-oriented possibilistic fuzzy C-Medoid clustering of human mobility patterns – Illustrative application for the Taxicab trips-based enrichment of public transport servicesPLOS ONE

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Additional Editor Comments (if provided):

The work is potentially interesting but it requires significant improvements.

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Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. Is the manuscript technically sound, and do the data support the conclusions?

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #1: Partly

Reviewer #2: Partly

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2. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: Yes

Reviewer #2: N/A

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3. Have the authors made all data underlying the findings in their manuscript fully available?

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #1: No

Reviewer #2: No

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4. Is the manuscript presented in an intelligible fashion and written in standard English?

PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.

Reviewer #1: No

Reviewer #2: Yes

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5. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #1: The idea and scope of the paper are interesting. In particular, the application of such a clustering algorithm with a tipicality function used to model people's willingness to walk to a bus stop is interesting.

However, the work is not mature enough. Both the introduction and results sections are often unclear, the experiments performed are quite poor, and the figures provided do not help at all at understanding.

In general, I think this work has potential, but it is not ready to be published.

Below specific comments:

- Introduction

Sometimes very confused. It is often not clear whether the authors are referring to something that has been done in another work or they are stating something not related to any another work. I would suggest to use the formula "Authors et al. [X] studied/analysed/stated/ ..." to let the reader understand that you are referring to someone else's work.

rows 4-6: "Based on these facts, innovative changes are needed to mitigate the effects of climate change within cities, and the transport sector there is one of the main contributors to greenhouse gas emissions"

this is not very clear, may be rephrased.

rows 31-33: "These GPS trajectories could be used to analyse the emission of particle matter from braking behaviours"

This statement is a bit out of context here. I would move it between the examples on how GPS trajectories can be used (from row 36 on).

row 47: I would add "In particular, electric buses [...]".

row 78-79: avoiding the ad-hoc installation of new stops is more of a choice than a major deficiency of clustering application for the design of public transportation lines. I would cite this as a decision made in the authors' paper, that has both a practical and a methodological motivation, but not as a deficiency of these particular clustering applications.

rows 110-113: "The developed PFCMD clustering algorithm that aims to cluster [...]" note clear, maybe a typo (remove "that"?)

- Materials and Methods

This section is very well written and clear.

eqs. (4) and (5): what does it mean "inA" in the end of the equation?

- Figures

In general, the figures are unintelligible: they have very low resolution, too small markers in the legend, it is almost impossible to even get the colors of the markers.

Fig. 1: colors in the legend (especially in the plot on the right) are unintelligible

Fig. 2: it seems it is missing the part of this figure referenced at row 297

Fig. 3: a zoom on the right hand side of the figure would definitely help. The figure as it stands is only useful for getting the outlier theme, but not all the rest.

- Results

rows 261-268: any reference / detail / experiment about the choice of m?

- Discussion

rows 343-344: "In our work, we demonstrate that Taxicab rides represent the human mobility patterns reasonably well (similarly to [18])." this does not seem the goal of the authors' work nor what they have done.

- References

Refs [14] and [21] refer to the same work

Refs [41] and [45] refer to the same work

Reviewer #2: In this paper, the authors propose a possibilistic fuzzy c-medoid clustering algorithm to study human mobility. The proposed medoid-based clustering approach groups the typical mobility patterns within walking distance to the stations of the public transportation system. Their results demonstrate that the mobility pattern is well-reflected. In fact, in the data recording (2014), there was no direct line to the airport in Hungary, which was implemented later in 2017.

The manuscript and the analysis have the potential to improve the knowledge in the human mobility field; however, I have some concerns about the methodology and some improvements that can be applied to increase the readability and the quality of the proposed manuscript:

1. The sentence starting in row 110 "The developed PFCMD clustering algorithm that aims to cluster.." seems to have an unnecessary “that”;

2. The introduction is sometimes not flowy, and it is not easy to understand what the references of some previous works refer to;

3. The time series analysis is not deep enough. I expect a deeper discussion about this crucial aspect for this work;

4. The clustering is performed for the taxi rides collected for a whole year, and after that, some public transport lines are suggested from the result of the clustering. I believe that the fact that the lines are indicated over an entire year's data and their influence on the study should be discussed better;

5. In line 156 I would say “the clustering is performed in the geographical domain” instead of “the clustering is performed in the spatial space”;

6. What is the “inA” at the end of equations 4 and 5? it is not clear to me;

7. The section “Temporal analysis of the resultant clusters” should be extended and described better;

8. In the sub-section “The number of public transportation lines, c:” the fact that the number of clusters may affect the number of lines is repeated and this may appear redundant. Furthermore, I suggest selecting c in such a way that optimizes a designed objective function;

9. How was the parameter m selected? it should be discussed;

10. How is the clustering quality measured?

11. In line 311 and 340 the authors stated “as seen/illustrated in Figure, …” the number of the Figure should be provided;

12. I think it is necessary to define an algorithm that performs the suggestions that can be made for the schedule of the lines. In general the rationale behind those choices are not that clear to me;

13. The quality of the Figures should be imporved to help the reader understand better some concepts of this manuscript, for example, they have a very low resolution and the markers in the legend are too small.

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Reviewer #1: Yes: Matteo Bohm

Reviewer #2: No

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Goal-oriented possibilistic fuzzy C-Medoid clustering of human mobility patterns – Illustrative application for the Taxicab trips-based enrichment of public transport services

PONE-D-22-03021R1

Dear Dr. Eigner,

We’re pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it meets all outstanding technical requirements.

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Kind regards,

Yajie Zou

Academic Editor

PLOS ONE

Additional Editor Comments (optional):

Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. If the authors have adequately addressed your comments raised in a previous round of review and you feel that this manuscript is now acceptable for publication, you may indicate that here to bypass the “Comments to the Author” section, enter your conflict of interest statement in the “Confidential to Editor” section, and submit your "Accept" recommendation.

Reviewer #1: All comments have been addressed

Reviewer #3: All comments have been addressed

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2. Is the manuscript technically sound, and do the data support the conclusions?

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #1: (No Response)

Reviewer #3: Yes

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3. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: (No Response)

Reviewer #3: Yes

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4. Have the authors made all data underlying the findings in their manuscript fully available?

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #1: (No Response)

Reviewer #3: Yes

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5. Is the manuscript presented in an intelligible fashion and written in standard English?

PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.

Reviewer #1: (No Response)

Reviewer #3: Yes

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6. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #1: (No Response)

Reviewer #3: (No Response)

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7. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files.

If you choose “no”, your identity will remain anonymous but your review may still be made public.

Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy.

Reviewer #1: No

Reviewer #3: No

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