An Entropy-Based Approach to Protecting Rating Systems from Unfair Testimonies
Summary :
How to mitigate the influence of unfair testimonies remains an open issue in the research of rating systems. Methods have been proposed to filter the unfair testimonies in order to mitigate the influence of unfair testimonies. However, existing methods depend on assumptions that ratings follow a particular distribution to carry out the testimony filtering. This constrains them in specific rating systems and hinders their applications in other reputation systems. Moreover, existing methods do not scale well with the increase of testimony number due to their iterative nature. In this paper, a novel entropy-based method is proposed to measure the testimony quality, based on which unfair testimonies are further filtered. The proposed method does not require the assumption regarding the rating distribution. Moreover, it scales linearly with the increase of the testimony number. Experimental results show that the proposed method is effective in mitigating the influence of various types of unfair testimonies.
- Publication
- IEICE TRANSACTIONS on Information Vol.E89-D No.9 pp.2502-2511
- Publication Date
- 2006/09/01
- Publicized
- Online ISSN
- 1745-1361
- DOI
- 10.1093/ietisy/e89-d.9.2502
- Type of Manuscript
- PAPER
- Category
- Contents Technology and Web Information Systems
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Jianshu WENG, Chunyan MIAO, Angela GOH, "An Entropy-Based Approach to Protecting Rating Systems from Unfair Testimonies" in IEICE TRANSACTIONS on Information,
vol. E89-D, no. 9, pp. 2502-2511, September 2006, doi: 10.1093/ietisy/e89-d.9.2502.
Abstract: How to mitigate the influence of unfair testimonies remains an open issue in the research of rating systems. Methods have been proposed to filter the unfair testimonies in order to mitigate the influence of unfair testimonies. However, existing methods depend on assumptions that ratings follow a particular distribution to carry out the testimony filtering. This constrains them in specific rating systems and hinders their applications in other reputation systems. Moreover, existing methods do not scale well with the increase of testimony number due to their iterative nature. In this paper, a novel entropy-based method is proposed to measure the testimony quality, based on which unfair testimonies are further filtered. The proposed method does not require the assumption regarding the rating distribution. Moreover, it scales linearly with the increase of the testimony number. Experimental results show that the proposed method is effective in mitigating the influence of various types of unfair testimonies.
URL: https://global.ieice.org/en_transactions/information/10.1093/ietisy/e89-d.9.2502/_p
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@ARTICLE{e89-d_9_2502,
author={Jianshu WENG, Chunyan MIAO, Angela GOH, },
journal={IEICE TRANSACTIONS on Information},
title={An Entropy-Based Approach to Protecting Rating Systems from Unfair Testimonies},
year={2006},
volume={E89-D},
number={9},
pages={2502-2511},
abstract={How to mitigate the influence of unfair testimonies remains an open issue in the research of rating systems. Methods have been proposed to filter the unfair testimonies in order to mitigate the influence of unfair testimonies. However, existing methods depend on assumptions that ratings follow a particular distribution to carry out the testimony filtering. This constrains them in specific rating systems and hinders their applications in other reputation systems. Moreover, existing methods do not scale well with the increase of testimony number due to their iterative nature. In this paper, a novel entropy-based method is proposed to measure the testimony quality, based on which unfair testimonies are further filtered. The proposed method does not require the assumption regarding the rating distribution. Moreover, it scales linearly with the increase of the testimony number. Experimental results show that the proposed method is effective in mitigating the influence of various types of unfair testimonies.},
keywords={},
doi={10.1093/ietisy/e89-d.9.2502},
ISSN={1745-1361},
month={September},}
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TY - JOUR
TI - An Entropy-Based Approach to Protecting Rating Systems from Unfair Testimonies
T2 - IEICE TRANSACTIONS on Information
SP - 2502
EP - 2511
AU - Jianshu WENG
AU - Chunyan MIAO
AU - Angela GOH
PY - 2006
DO - 10.1093/ietisy/e89-d.9.2502
JO - IEICE TRANSACTIONS on Information
SN - 1745-1361
VL - E89-D
IS - 9
JA - IEICE TRANSACTIONS on Information
Y1 - September 2006
AB - How to mitigate the influence of unfair testimonies remains an open issue in the research of rating systems. Methods have been proposed to filter the unfair testimonies in order to mitigate the influence of unfair testimonies. However, existing methods depend on assumptions that ratings follow a particular distribution to carry out the testimony filtering. This constrains them in specific rating systems and hinders their applications in other reputation systems. Moreover, existing methods do not scale well with the increase of testimony number due to their iterative nature. In this paper, a novel entropy-based method is proposed to measure the testimony quality, based on which unfair testimonies are further filtered. The proposed method does not require the assumption regarding the rating distribution. Moreover, it scales linearly with the increase of the testimony number. Experimental results show that the proposed method is effective in mitigating the influence of various types of unfair testimonies.
ER -
English
