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Application of Liquid Rank Reputation System for Content Recommendation. / Saxena, Abhishek; Kolonin, Anton.

Proceedings - 2022 Ural Symposium on Biomedical Engineering, Radioelectronics and Information Technology, USBEREIT 2022. Institute of Electrical and Electronics Engineers Inc., 2022. p. 196-199 (Proceedings - 2022 Ural Symposium on Biomedical Engineering, Radioelectronics and Information Technology, USBEREIT 2022).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Research › peer-review

Harvard

Saxena, A & Kolonin, A 2022, Application of Liquid Rank Reputation System for Content Recommendation. in Proceedings - 2022 Ural Symposium on Biomedical Engineering, Radioelectronics and Information Technology, USBEREIT 2022. Proceedings - 2022 Ural Symposium on Biomedical Engineering, Radioelectronics and Information Technology, USBEREIT 2022, Institute of Electrical and Electronics Engineers Inc., pp. 196-199, 2022 Ural Symposium on Biomedical Engineering, Radioelectronics and Information Technology, USBEREIT 2022, Yekaterinburg, Russian Federation, 19.09.2022. https://doi.org/10.1109/USBEREIT56278.2022.9923352

APA

Saxena, A., & Kolonin, A. (2022). Application of Liquid Rank Reputation System for Content Recommendation. In Proceedings - 2022 Ural Symposium on Biomedical Engineering, Radioelectronics and Information Technology, USBEREIT 2022 (pp. 196-199). (Proceedings - 2022 Ural Symposium on Biomedical Engineering, Radioelectronics and Information Technology, USBEREIT 2022). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/USBEREIT56278.2022.9923352

Vancouver

Saxena A, Kolonin A. Application of Liquid Rank Reputation System for Content Recommendation. In Proceedings - 2022 Ural Symposium on Biomedical Engineering, Radioelectronics and Information Technology, USBEREIT 2022. Institute of Electrical and Electronics Engineers Inc. 2022. p. 196-199. (Proceedings - 2022 Ural Symposium on Biomedical Engineering, Radioelectronics and Information Technology, USBEREIT 2022). doi: 10.1109/USBEREIT56278.2022.9923352

Author

Saxena, Abhishek ; Kolonin, Anton. / Application of Liquid Rank Reputation System for Content Recommendation. Proceedings - 2022 Ural Symposium on Biomedical Engineering, Radioelectronics and Information Technology, USBEREIT 2022. Institute of Electrical and Electronics Engineers Inc., 2022. pp. 196-199 (Proceedings - 2022 Ural Symposium on Biomedical Engineering, Radioelectronics and Information Technology, USBEREIT 2022).

BibTeX

@inproceedings{91b0bf7e6434450786e81e593dffdd2b,
title = "Application of Liquid Rank Reputation System for Content Recommendation",
abstract = "An effective content recommendation on social media platforms should be able to benefit both creators to earn fair compensation and consumers to enjoy really relevant, interesting, and personalized content. In this paper, we propose a model to implement the liquid democracy principle for the content recommendation system. It uses a personalized content recommendation model based on reputation ranking system to encourage personal interests driven recommendation. Moreover, the personalization factors to an end users' higher-order friends on the social network (initial input Twitter channels in our case study) to improve the accuracy and diversity of recommendation results. This paper analyzes the dataset based on cryptocurrency news on Twitter to find the opinion leader using the liquid rank reputation system. This paper deals with the tier-2 implementation of a liquid rank in a content recommendation model. This model can be also used as an additional layer in the other recommendation systems. The paper proposes the implementation, challenges, and future scope of the liquid rank reputation model.",
keywords = "liquid democracy, peer-to-peer systems, recommendation systems, reputation system, social computing",
author = "Abhishek Saxena and Anton Kolonin",
note = "Publisher Copyright: {\textcopyright} 2022 IEEE.; 2022 Ural Symposium on Biomedical Engineering, Radioelectronics and Information Technology, USBEREIT 2022 ; Conference date: 19-09-2022 Through 21-09-2022",
year = "2022",
month = nov,
day = "3",
doi = "10.1109/USBEREIT56278.2022.9923352",
language = "English",
series = "Proceedings - 2022 Ural Symposium on Biomedical Engineering, Radioelectronics and Information Technology, USBEREIT 2022",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "196--199",
booktitle = "Proceedings - 2022 Ural Symposium on Biomedical Engineering, Radioelectronics and Information Technology, USBEREIT 2022",
address = "United States",

}

RIS

TY - GEN

T1 - Application of Liquid Rank Reputation System for Content Recommendation

AU - Saxena, Abhishek

AU - Kolonin, Anton

N1 - Publisher Copyright: © 2022 IEEE.

PY - 2022/11/3

Y1 - 2022/11/3

N2 - An effective content recommendation on social media platforms should be able to benefit both creators to earn fair compensation and consumers to enjoy really relevant, interesting, and personalized content. In this paper, we propose a model to implement the liquid democracy principle for the content recommendation system. It uses a personalized content recommendation model based on reputation ranking system to encourage personal interests driven recommendation. Moreover, the personalization factors to an end users' higher-order friends on the social network (initial input Twitter channels in our case study) to improve the accuracy and diversity of recommendation results. This paper analyzes the dataset based on cryptocurrency news on Twitter to find the opinion leader using the liquid rank reputation system. This paper deals with the tier-2 implementation of a liquid rank in a content recommendation model. This model can be also used as an additional layer in the other recommendation systems. The paper proposes the implementation, challenges, and future scope of the liquid rank reputation model.

AB - An effective content recommendation on social media platforms should be able to benefit both creators to earn fair compensation and consumers to enjoy really relevant, interesting, and personalized content. In this paper, we propose a model to implement the liquid democracy principle for the content recommendation system. It uses a personalized content recommendation model based on reputation ranking system to encourage personal interests driven recommendation. Moreover, the personalization factors to an end users' higher-order friends on the social network (initial input Twitter channels in our case study) to improve the accuracy and diversity of recommendation results. This paper analyzes the dataset based on cryptocurrency news on Twitter to find the opinion leader using the liquid rank reputation system. This paper deals with the tier-2 implementation of a liquid rank in a content recommendation model. This model can be also used as an additional layer in the other recommendation systems. The paper proposes the implementation, challenges, and future scope of the liquid rank reputation model.

KW - liquid democracy

KW - peer-to-peer systems

KW - recommendation systems

KW - reputation system

KW - social computing

UR - http://www.scopus.com/inward/record.url?scp=85141845691&partnerID=8YFLogxK

UR - https://www.mendeley.com/catalogue/4c8eae57-2b38-35d9-af6f-ce19018e62cf/

U2 - 10.1109/USBEREIT56278.2022.9923352

DO - 10.1109/USBEREIT56278.2022.9923352

M3 - Conference contribution

AN - SCOPUS:85141845691

T3 - Proceedings - 2022 Ural Symposium on Biomedical Engineering, Radioelectronics and Information Technology, USBEREIT 2022

SP - 196

EP - 199

BT - Proceedings - 2022 Ural Symposium on Biomedical Engineering, Radioelectronics and Information Technology, USBEREIT 2022

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 2022 Ural Symposium on Biomedical Engineering, Radioelectronics and Information Technology, USBEREIT 2022

Y2 - 19 September 2022 through 21 September 2022

ER -

ID: 39471981