PONE-D-21-04507

An Interpretable Framework for Investigating Neighborhood Effect in POI Recommendation

PLOS ONE

Dear Dr. Murukannaiah,

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PLOS ONE

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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: Yes

Reviewer #2: Yes

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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: Yes

Reviewer #2: Yes

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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: Yes

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 manuscript describes a new method to incorporate the neighborhood information when predicting a user's preference of a point-of-interest. The overall writing is fine and the authors have explained the functions used in different features.

Few comments are listed below:

1. A bit of confusing about the number of times a user visits a POI. At lines 148-149, the authors said that "... not the exact number if the user visited the POI more than once.", but in Table 2, n_{u,l} is the number of times a user u visits POI l. Please clarify.

2. Lines 160-162, the size of a neighborhood is the number of POIs within a distance, e.g. 100 m, 200 m, 500 m. This doesn't equal to the description at lines 161-162. There might be cases that the distance is larger, but no POIs are included.

3. Lines 202-204, is there any reason why a word has to be appeared at least four times in a city? For example, why not five times?

4. Line 421, is the method "IRenMF"? The subtitle is the same as line 430.

5. Lines 463-464, "... the embedding size of users (POIs) is 16 ...", should it be 32, as indicated at line 463?

6. Please indicate the meaning of bold text in tables, are they the best values in the corresponding categories?

Reviewer #2: This manuscript addresses a problem of recommending potential points of interest (POIs) to users. The particular emphasis is on a phenomenon called the "neighborhood effect" that relates to a user's preference for POIs in the neighborhood of a POI whose preference is already established. The authors accomplish two tasks. First, they identify features potentially related to the neighborhood effect and employ both logistic regression and FastTree to evaluate combinations of features. Second, they develop an artificial neural network (ANN) model meant to take advantage of the neighborhood effect and evaluate it against some established matrix factorization techniques and a simplified ANN. At a high level, the research seems good and the results correct, but I do have some detailed comments and thoughts to address.

First, I marked up some required changes in red on the manuscript and scanned the result to a PDF, which is attached. Note that "data set" is properly two words, though this is often abused.

Second, many of the references are on the older side; the manuscript would be improved by refreshing the References list with more recent papers.

Third, on page 5, the manuscript makes an offhand remark about a frequency distribution being a power law. This kind of casual remark is often made without justification, as is done here. It is likely the distribution is not a true power law in a statisitical sense, so it is best to delete this claim.

Fourth, there is little to no justification for the ANN architecture (Section 6.1); it is just stated as a fact. This approach is common in ANN research and does not reflect well on the area. Answer why you made the architectural decisions you did in a deeper way.

Fifth, the Problem Formulation (Section 3) is merely two sets of questions. There is no real statement of computer science problems, where the inputs and outputs (solutions) are mathematically specified so that the authors and the readers can know when a problem is solved. I note that the authors are all computer scientists, so they know how to mathematically specify computational problems. Such specifications should be developed in any revision.

Sixth and finally, I never saw a mathematical definition of the neighborhood effect, so it was never clear what it really is; this should be fixed in any revision.

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Reviewer #1: No

Reviewer #2: No

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Attachments

Attachment

Submitted filename: Yuan_scanned_PLOSOne.pdf

An Interpretable Framework for Investigating Neighborhood Effect in POI Recommendation

PONE-D-21-04507R1

Dear Dr. Murukannaiah,

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.

Within one week, you’ll receive an e-mail detailing the required amendments. When these have been addressed, you’ll receive a formal acceptance letter and your manuscript will be scheduled for publication.

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Kind regards,

Haoran Xie

Academic Editor

PLOS ONE

Additional Editor Comments (optional):

The paper is ready for publication.

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 #2: 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 #2: Yes

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

Reviewer #1: (No Response)

Reviewer #2: N/A

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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 #2: 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 #2: 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 #2: (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 #2: Yes: Lenwood S. Heath