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Peer-Review Record

Expert Finding Considering Dynamic Profiles and Trust in Social Networks

Electronics 2019, 8(10), 1165; https://doi.org/10.3390/electronics8101165
by Kyoungsoo Bok 1, Inbae Jeon 2, Jongtae Lim 2 and Jaesoo Yoo 2,*
Reviewer 1: Anonymous
Reviewer 2: Anonymous
Electronics 2019, 8(10), 1165; https://doi.org/10.3390/electronics8101165
Submission received: 24 September 2019 / Revised: 2 October 2019 / Accepted: 13 October 2019 / Published: 15 October 2019
(This article belongs to the Section Computer Science & Engineering)

Round 1

Reviewer 1 Report

The study focuses on the expert finding considering dynamic profile and 2 trust in social networks. The paper shows good theoretical and practical background.

My main attention to the paper is that:
1. The paper needs additional formatting in some places.
2. On the end of Equations (1-11) must be "dot".
3. Which type of programming language (software, Matlab, Python or other) was used? Please explain why?
4. It's possible to compare these results with artificial neural networks?
5. How performance evaluation depends on computer parameters?
6. Please explain more deeply this sentence (pg. 11., lines: 330-333 ) <The finding processing speed is very fast, and the time taken to find is consistent regardless of the number of users in the existing simple matching scheme, since it only compares the question and areas of interest in user profiles.>

Author Response

Please see the attachment.

Thank you for your good comments.

Jaesoo Yoo

Author Response File: Author Response.pdf

Reviewer 2 Report

The authors deal with the problem of untrustworthy information sharing. Bok et al. propose an expert finding scheme based dynamic profile and trust in social networks.

They overcome many of the shortcomings associated with existing schemes in literature. Rather than using the existing profiles of users, accuracy and trust are obtained by a server that periodically creates dynamic user profiles through the analysis of users’ recent activities, and reputation scores and reply qualities of users.

Finally, the authors verify effectiveness and practicability of the algorithm with various experiments.

 

The introduction and section 3 have a high similarity to the authors' own article in BIGCOMP proceedings:

Kyoungsoo Bok, Inbae Jeon, Jongtae Lim, Jaesoo Yoo. "An expert search scheme using user activities and reliabilities in social networks", 2015 International Conference on Big Data and Smart Computing, 2015.

 

The layout of all formulas must be improved (size of variables and subscripts, use of fractions, etc.)

The motivation and justification of the work are appropriate. The paper is well written in correct English. The examples included are adequate.

 

Now I include some typographical errors:

 

Pg. 10, line: 327

For: the expert’s profile use the scheme

read: the expert’s profile uses the scheme

 

In ref. 8

For: Wor dNet dictionary

read: WordNet dictionary

 

In ref. 41

For: Itrust

read: iTrust

Author Response

Please see the attachment.

Thank you for your good comments.

Jaesoo Yoo

Author Response File: Author Response.pdf

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