A Reputation Ranking Method based on Rating Patterns and Rating Deviation

Jian Zhou; Yu Feng Liu; Hong Liang Sun

doi:10.1109/DSIT55514.2022.9943923

A Reputation Ranking Method based on Rating Patterns and Rating Deviation

Jian Zhou
, Yu Feng Liu
, Hong Liang Sun

School of Computer Science

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

5 Citations (Scopus)

Abstract

In the e-commerce platform, user purchase behavior often depends on personal experience and the objective ratings of others. Various businesses employ a large number of spammers to obtain illegal benefits by distorting the ranking of goods, which seriously affects the market order. How to design a high- speed and effective ranking method to remove these spammers is necessary and significant. In this paper, a novel reputation ranking method is proposed based on users' Rating Patterns and Rating Deviation (RPRD) because users' rating preference and historical behavior differ significantly with spammers. We compare RPRD method with three classical methods Deviation- based Ranking (DR), Iterative Group-based Ranking (IGR) and Iterative Balance Ranking (IBR) on three real datasets. Experimental results show that the RPRD method can effectively resist spammers attack and identification, especially in detecting random spammers. On the other hand, this method always has high accuracy and robustness even if the network is relatively sparse. It can also be applied in large and sparse bipartite rating networks in a short time.

Original language	English
Title of host publication	2022 5th International Conference on Data Science and Information Technology, DSIT 2022 - Proceedings
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)	9781665498685
DOIs	https://doi.org/10.1109/DSIT55514.2022.9943923
Publication status	Published - 2022
Event	5th International Conference on Data Science and Information Technology, DSIT 2022 - Shanghai, China Duration: 22 Jul 2022 → 24 Jul 2022

Publication series

Name	2022 5th International Conference on Data Science and Information Technology, DSIT 2022 - Proceedings

Conference

Conference	5th International Conference on Data Science and Information Technology, DSIT 2022
Country/Territory	China
City	Shanghai
Period	22/07/22 → 24/07/22

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 16 Peace, Justice and Strong Institutions

Free Keywords

Fraud Detection
Rating Patterns
Spammers Attack

ASJC Scopus subject areas

Artificial Intelligence
Computer Science Applications
Computer Vision and Pattern Recognition
Information Systems
Decision Sciences (miscellaneous)
Information Systems and Management
Statistics, Probability and Uncertainty

Access to Document

10.1109/DSIT55514.2022.9943923

Cite this

Zhou, J., Liu, Y. F., & Sun, H. L. (2022). A Reputation Ranking Method based on Rating Patterns and Rating Deviation. In 2022 5th International Conference on Data Science and Information Technology, DSIT 2022 - Proceedings (2022 5th International Conference on Data Science and Information Technology, DSIT 2022 - Proceedings). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/DSIT55514.2022.9943923

Zhou, Jian ; Liu, Yu Feng ; Sun, Hong Liang. / A Reputation Ranking Method based on Rating Patterns and Rating Deviation. 2022 5th International Conference on Data Science and Information Technology, DSIT 2022 - Proceedings. Institute of Electrical and Electronics Engineers Inc., 2022. (2022 5th International Conference on Data Science and Information Technology, DSIT 2022 - Proceedings).

@inproceedings{290a909eff9543a19acc1ed66ac1bf16,

title = "A Reputation Ranking Method based on Rating Patterns and Rating Deviation",

abstract = "In the e-commerce platform, user purchase behavior often depends on personal experience and the objective ratings of others. Various businesses employ a large number of spammers to obtain illegal benefits by distorting the ranking of goods, which seriously affects the market order. How to design a high- speed and effective ranking method to remove these spammers is necessary and significant. In this paper, a novel reputation ranking method is proposed based on users' Rating Patterns and Rating Deviation (RPRD) because users' rating preference and historical behavior differ significantly with spammers. We compare RPRD method with three classical methods Deviation- based Ranking (DR), Iterative Group-based Ranking (IGR) and Iterative Balance Ranking (IBR) on three real datasets. Experimental results show that the RPRD method can effectively resist spammers attack and identification, especially in detecting random spammers. On the other hand, this method always has high accuracy and robustness even if the network is relatively sparse. It can also be applied in large and sparse bipartite rating networks in a short time.",

keywords = "Fraud Detection, Rating Patterns, Spammers Attack",

author = "Jian Zhou and Liu, \{Yu Feng\} and Sun, \{Hong Liang\}",

note = "Publisher Copyright: {\textcopyright} 2022 IEEE.; 5th International Conference on Data Science and Information Technology, DSIT 2022 ; Conference date: 22-07-2022 Through 24-07-2022",

year = "2022",

doi = "10.1109/DSIT55514.2022.9943923",

language = "English",

series = "2022 5th International Conference on Data Science and Information Technology, DSIT 2022 - Proceedings",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

booktitle = "2022 5th International Conference on Data Science and Information Technology, DSIT 2022 - Proceedings",

address = "United States",

}

Zhou, J, Liu, YF & Sun, HL 2022, A Reputation Ranking Method based on Rating Patterns and Rating Deviation. in 2022 5th International Conference on Data Science and Information Technology, DSIT 2022 - Proceedings. 2022 5th International Conference on Data Science and Information Technology, DSIT 2022 - Proceedings, Institute of Electrical and Electronics Engineers Inc., 5th International Conference on Data Science and Information Technology, DSIT 2022, Shanghai, China, 22/07/22. https://doi.org/10.1109/DSIT55514.2022.9943923

A Reputation Ranking Method based on Rating Patterns and Rating Deviation. / Zhou, Jian; Liu, Yu Feng; Sun, Hong Liang.
2022 5th International Conference on Data Science and Information Technology, DSIT 2022 - Proceedings. Institute of Electrical and Electronics Engineers Inc., 2022. (2022 5th International Conference on Data Science and Information Technology, DSIT 2022 - Proceedings).

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

TY - GEN

T1 - A Reputation Ranking Method based on Rating Patterns and Rating Deviation

AU - Zhou, Jian

AU - Liu, Yu Feng

AU - Sun, Hong Liang

PY - 2022

Y1 - 2022

N2 - In the e-commerce platform, user purchase behavior often depends on personal experience and the objective ratings of others. Various businesses employ a large number of spammers to obtain illegal benefits by distorting the ranking of goods, which seriously affects the market order. How to design a high- speed and effective ranking method to remove these spammers is necessary and significant. In this paper, a novel reputation ranking method is proposed based on users' Rating Patterns and Rating Deviation (RPRD) because users' rating preference and historical behavior differ significantly with spammers. We compare RPRD method with three classical methods Deviation- based Ranking (DR), Iterative Group-based Ranking (IGR) and Iterative Balance Ranking (IBR) on three real datasets. Experimental results show that the RPRD method can effectively resist spammers attack and identification, especially in detecting random spammers. On the other hand, this method always has high accuracy and robustness even if the network is relatively sparse. It can also be applied in large and sparse bipartite rating networks in a short time.

AB - In the e-commerce platform, user purchase behavior often depends on personal experience and the objective ratings of others. Various businesses employ a large number of spammers to obtain illegal benefits by distorting the ranking of goods, which seriously affects the market order. How to design a high- speed and effective ranking method to remove these spammers is necessary and significant. In this paper, a novel reputation ranking method is proposed based on users' Rating Patterns and Rating Deviation (RPRD) because users' rating preference and historical behavior differ significantly with spammers. We compare RPRD method with three classical methods Deviation- based Ranking (DR), Iterative Group-based Ranking (IGR) and Iterative Balance Ranking (IBR) on three real datasets. Experimental results show that the RPRD method can effectively resist spammers attack and identification, especially in detecting random spammers. On the other hand, this method always has high accuracy and robustness even if the network is relatively sparse. It can also be applied in large and sparse bipartite rating networks in a short time.

KW - Fraud Detection

KW - Rating Patterns

KW - Spammers Attack

UR - https://www.scopus.com/pages/publications/85143131398

U2 - 10.1109/DSIT55514.2022.9943923

DO - 10.1109/DSIT55514.2022.9943923

M3 - Conference contribution

AN - SCOPUS:85143131398

T3 - 2022 5th International Conference on Data Science and Information Technology, DSIT 2022 - Proceedings

BT - 2022 5th International Conference on Data Science and Information Technology, DSIT 2022 - Proceedings

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 5th International Conference on Data Science and Information Technology, DSIT 2022

Y2 - 22 July 2022 through 24 July 2022

ER -

Zhou J, Liu YF, Sun HL. A Reputation Ranking Method based on Rating Patterns and Rating Deviation. In 2022 5th International Conference on Data Science and Information Technology, DSIT 2022 - Proceedings. Institute of Electrical and Electronics Engineers Inc. 2022. (2022 5th International Conference on Data Science and Information Technology, DSIT 2022 - Proceedings). doi: 10.1109/DSIT55514.2022.9943923

A Reputation Ranking Method based on Rating Patterns and Rating Deviation

Abstract

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UN SDGs

Free Keywords

ASJC Scopus subject areas

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