Reputation Systems in E-commerce: Comparative Analysis and Perspectives to Model Uncertainty Inherent in Them
E-commerce is a runaway activity growing at an unprecedented rate all over the world and drawing millions of people from different spots on the globe. At the same time, e-commerce affords ground for malicious behavior that becomes a subject of principal concern. One way to minimize this threat is to...
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Ivannikov Institute for System Programming of the Russian Academy of Sciences
2019-09-01
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doaj-e1be53fd29104a9f8bd10a44c046e5202020-11-25T02:06:24Zeng Ivannikov Institute for System Programming of the Russian Academy of SciencesТруды Института системного программирования РАН2079-81562220-64262019-09-013139912210.15514/ISPRAS-2019-31(3)-91169Reputation Systems in E-commerce: Comparative Analysis and Perspectives to Model Uncertainty Inherent in ThemMikhail Mikhailovitch Nosovsyi0Konstantin Yurievitch Degtiarev1Национальный исследовательский университет «Высшая школа экономики»Национальный исследовательский университет «Высшая школа экономики»E-commerce is a runaway activity growing at an unprecedented rate all over the world and drawing millions of people from different spots on the globe. At the same time, e-commerce affords ground for malicious behavior that becomes a subject of principal concern. One way to minimize this threat is to use reputation systems for trust management across users of the network. Most of existing reputation systems are feedback-based, and they work with feedback expressed in the form of numbers (i.e. from 0 to 5 as per integer scale). In general, notions of trust and reputation exemplify uncertain (imprecise) pieces of information (data) that are typical for the field of e-commerce. We suggest using fuzzy logic approach to take into account the inherent vagueness of user’s feedback expressing the degree of satisfaction after completion of a regular transaction. Brief comparative analysis of well-known reputation systems, such as EigenTrust, HonestPeer, Absolute Trust, PowerTrust and PeerTrust systems is presented. Based on marked out criteria like convergence speed, robustness, the presence of hyper parameters, the most robust and scalable algorithm is chosen on the basis of carried out sets of computer experiments. The examples of chosen algorithm’s (PeerTrust) fuzzy versions (both Type-1 and Interval Type-2 cases) are implemented and analysed.https://ispranproceedings.elpub.ru/jour/article/view/1182электронная коммерциярепутационная системапиринговые вычисленияуправление довериемнечеткостьнечеткая логикалингвистическая переменнаянечеткое множество 1-го типанечеткое множество 2-го типа |
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language |
English |
format |
Article |
sources |
DOAJ |
author |
Mikhail Mikhailovitch Nosovsyi Konstantin Yurievitch Degtiarev |
spellingShingle |
Mikhail Mikhailovitch Nosovsyi Konstantin Yurievitch Degtiarev Reputation Systems in E-commerce: Comparative Analysis and Perspectives to Model Uncertainty Inherent in Them Труды Института системного программирования РАН электронная коммерция репутационная система пиринговые вычисления управление доверием нечеткость нечеткая логика лингвистическая переменная нечеткое множество 1-го типа нечеткое множество 2-го типа |
author_facet |
Mikhail Mikhailovitch Nosovsyi Konstantin Yurievitch Degtiarev |
author_sort |
Mikhail Mikhailovitch Nosovsyi |
title |
Reputation Systems in E-commerce: Comparative Analysis and Perspectives to Model Uncertainty Inherent in Them |
title_short |
Reputation Systems in E-commerce: Comparative Analysis and Perspectives to Model Uncertainty Inherent in Them |
title_full |
Reputation Systems in E-commerce: Comparative Analysis and Perspectives to Model Uncertainty Inherent in Them |
title_fullStr |
Reputation Systems in E-commerce: Comparative Analysis and Perspectives to Model Uncertainty Inherent in Them |
title_full_unstemmed |
Reputation Systems in E-commerce: Comparative Analysis and Perspectives to Model Uncertainty Inherent in Them |
title_sort |
reputation systems in e-commerce: comparative analysis and perspectives to model uncertainty inherent in them |
publisher |
Ivannikov Institute for System Programming of the Russian Academy of Sciences |
series |
Труды Института системного программирования РАН |
issn |
2079-8156 2220-6426 |
publishDate |
2019-09-01 |
description |
E-commerce is a runaway activity growing at an unprecedented rate all over the world and drawing millions of people from different spots on the globe. At the same time, e-commerce affords ground for malicious behavior that becomes a subject of principal concern. One way to minimize this threat is to use reputation systems for trust management across users of the network. Most of existing reputation systems are feedback-based, and they work with feedback expressed in the form of numbers (i.e. from 0 to 5 as per integer scale). In general, notions of trust and reputation exemplify uncertain (imprecise) pieces of information (data) that are typical for the field of e-commerce. We suggest using fuzzy logic approach to take into account the inherent vagueness of user’s feedback expressing the degree of satisfaction after completion of a regular transaction. Brief comparative analysis of well-known reputation systems, such as EigenTrust, HonestPeer, Absolute Trust, PowerTrust and PeerTrust systems is presented. Based on marked out criteria like convergence speed, robustness, the presence of hyper parameters, the most robust and scalable algorithm is chosen on the basis of carried out sets of computer experiments. The examples of chosen algorithm’s (PeerTrust) fuzzy versions (both Type-1 and Interval Type-2 cases) are implemented and analysed. |
topic |
электронная коммерция репутационная система пиринговые вычисления управление доверием нечеткость нечеткая логика лингвистическая переменная нечеткое множество 1-го типа нечеткое множество 2-го типа |
url |
https://ispranproceedings.elpub.ru/jour/article/view/1182 |
work_keys_str_mv |
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