Identification of user profiles in online social networks › Научные исследования в СПбГУ

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Identification of user profiles in online social networks : A combined approach with face recognition. / Oliseenko, V. D.; Abramov, M. V.

в: Journal of Physics: Conference Series, Том 1864, № 1, 012119, 01.05.2021.

Результаты исследований: Научные публикации в периодических изданиях › статья в журнале по материалам конференции › Рецензирование

BibTeX

@article{6feb273c46c44876bb81993e9c912703,

title = "Identification of user profiles in online social networks: A combined approach with face recognition",

abstract = "This paper suggests improving the previously existing method of identifying user profiles in different online social networks by adding face recognition results to the model. It is assumed that the method will become more stable for identifying people with the same name, city and age. It will help to find more user profiles in different online social networks, which will improve the estimation of their personal characteristics. Evaluating user personality traits is one of the key tasks in protecting employees of enterprises and companies from social engineering attacks.",

author = "Oliseenko, {V. D.} and Abramov, {M. V.}",

note = "Publisher Copyright: {\textcopyright} Published under licence by IOP Publishing Ltd. Copyright: Copyright 2021 Elsevier B.V., All rights reserved.; 13th Multiconference on Control Problems, MCCP 2020 ; Conference date: 06-10-2020 Through 08-10-2020",

year = "2021",

month = may,

day = "1",

doi = "10.1088/1742-6596/1864/1/012119",

language = "English",

volume = "1864",

journal = "Journal of Physics: Conference Series",

issn = "1742-6588",

publisher = "IOP Publishing Ltd.",

number = "1",

url = "http://www.elektropribor.spb.ru/nauchnaya-deyatelnost/xiii-mkpu/index3.php",

}

RIS

TY - JOUR

T1 - Identification of user profiles in online social networks

T2 - 13th Multiconference on Control Problems, MCCP 2020

AU - Oliseenko, V. D.

AU - Abramov, M. V.

N1 - Conference code: 13

PY - 2021/5/1

Y1 - 2021/5/1

N2 - This paper suggests improving the previously existing method of identifying user profiles in different online social networks by adding face recognition results to the model. It is assumed that the method will become more stable for identifying people with the same name, city and age. It will help to find more user profiles in different online social networks, which will improve the estimation of their personal characteristics. Evaluating user personality traits is one of the key tasks in protecting employees of enterprises and companies from social engineering attacks.

AB - This paper suggests improving the previously existing method of identifying user profiles in different online social networks by adding face recognition results to the model. It is assumed that the method will become more stable for identifying people with the same name, city and age. It will help to find more user profiles in different online social networks, which will improve the estimation of their personal characteristics. Evaluating user personality traits is one of the key tasks in protecting employees of enterprises and companies from social engineering attacks.

UR - http://www.scopus.com/inward/record.url?scp=85107416104&partnerID=8YFLogxK

U2 - 10.1088/1742-6596/1864/1/012119

DO - 10.1088/1742-6596/1864/1/012119

M3 - Conference article

AN - SCOPUS:85107416104

VL - 1864

JO - Journal of Physics: Conference Series

JF - Journal of Physics: Conference Series

SN - 1742-6588

IS - 1

M1 - 012119

Y2 - 6 October 2020 through 8 October 2020

ER -

ID: 77992526

Identification of user profiles in online social networks: A combined approach with face recognition

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