Extensive Experimental Validation of a Personalized Approach for Coping with Unfair Ratings in Reputation Systems

The unfair rating problem exists when a buying agent models the trustworthiness of selling agents by also relying on ratings of the sellers from other buyers in electronic marketplaces, that is in a reputation system. In this article, we first analyze the capabilities of existing approaches for copi...

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Autor principal:	Zhang,Jie
Lenguaje:	English
Publicado:	Universidad de Talca 2011
Materias:	Trust and reputation systems Unfair ratings Electronic marketplaces Probabilistic reasoning approaches Multi-agent systems
Acceso en línea:	http://www.scielo.cl/scielo.php?script=sci_arttext&pid=S0718-18762011000300005
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spelling	oai:scielo:S0718-187620110003000052018-10-12Extensive Experimental Validation of a Personalized Approach for Coping with Unfair Ratings in Reputation SystemsZhang,Jie Trust and reputation systems Unfair ratings Electronic marketplaces Probabilistic reasoning approaches Multi-agent systems The unfair rating problem exists when a buying agent models the trustworthiness of selling agents by also relying on ratings of the sellers from other buyers in electronic marketplaces, that is in a reputation system. In this article, we first analyze the capabilities of existing approaches for coping with unfair ratings in different challenging scenarios, including ones where the majority of buyers are dishonest, buyers lack personal experience with sellers, sellers may vary their behavior, and buyers may provide a large number of ratings. We then present a personalized modeling approach (PMA) that has all these capabilities. Our approach allows a buyer to model both the private reputation and public reputation of other buyers to determine whether these buyers’ ratings are fair. More importantly, in this work, we focus on experimental comparison of our approach with two key models in a simulated dynamic e-marketplace environment. We specifically examine the above mentioned scenarios to confirm our analysis and to demonstrate the capabilities of our approach. Our study thus provides the extensive experimental support for the personalized approach that can be effectively employed by reputation systems to cope with unfair ratings.info:eu-repo/semantics/openAccessUniversidad de TalcaJournal of theoretical and applied electronic commerce research v.6 n.3 20112011-12-01text/htmlhttp://www.scielo.cl/scielo.php?script=sci_arttext&pid=S0718-18762011000300005en10.4067/S0718-18762011000300005
institution	Scielo Chile
collection	Scielo Chile
language	English
topic	Trust and reputation systems Unfair ratings Electronic marketplaces Probabilistic reasoning approaches Multi-agent systems
spellingShingle	Trust and reputation systems Unfair ratings Electronic marketplaces Probabilistic reasoning approaches Multi-agent systems Zhang,Jie Extensive Experimental Validation of a Personalized Approach for Coping with Unfair Ratings in Reputation Systems
description	The unfair rating problem exists when a buying agent models the trustworthiness of selling agents by also relying on ratings of the sellers from other buyers in electronic marketplaces, that is in a reputation system. In this article, we first analyze the capabilities of existing approaches for coping with unfair ratings in different challenging scenarios, including ones where the majority of buyers are dishonest, buyers lack personal experience with sellers, sellers may vary their behavior, and buyers may provide a large number of ratings. We then present a personalized modeling approach (PMA) that has all these capabilities. Our approach allows a buyer to model both the private reputation and public reputation of other buyers to determine whether these buyers’ ratings are fair. More importantly, in this work, we focus on experimental comparison of our approach with two key models in a simulated dynamic e-marketplace environment. We specifically examine the above mentioned scenarios to confirm our analysis and to demonstrate the capabilities of our approach. Our study thus provides the extensive experimental support for the personalized approach that can be effectively employed by reputation systems to cope with unfair ratings.
author	Zhang,Jie
author_facet	Zhang,Jie
author_sort	Zhang,Jie
title	Extensive Experimental Validation of a Personalized Approach for Coping with Unfair Ratings in Reputation Systems
title_short	Extensive Experimental Validation of a Personalized Approach for Coping with Unfair Ratings in Reputation Systems
title_full	Extensive Experimental Validation of a Personalized Approach for Coping with Unfair Ratings in Reputation Systems
title_fullStr	Extensive Experimental Validation of a Personalized Approach for Coping with Unfair Ratings in Reputation Systems
title_full_unstemmed	Extensive Experimental Validation of a Personalized Approach for Coping with Unfair Ratings in Reputation Systems
title_sort	extensive experimental validation of a personalized approach for coping with unfair ratings in reputation systems
publisher	Universidad de Talca
publishDate	2011
url	http://www.scielo.cl/scielo.php?script=sci_arttext&pid=S0718-18762011000300005
work_keys_str_mv	AT zhangjie extensiveexperimentalvalidationofapersonalizedapproachforcopingwithunfairratingsinreputationsystems
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Extensive Experimental Validation of a Personalized Approach for Coping with Unfair Ratings in Reputation Systems

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