In this paper, we propose a biclustering-based approach to iden-tify dishonest advisors (who provide misleading opinions about sellers), while evaluating seller trustworthiness on multiple crite-ria. It considers correlation between advisors ’ ratings to various criteria and trust transitivity to accurately filter the dishonest advi-sors. Evaluation results demonstrate the robustness of our approach against various types of unfair rating attacks
In this paper, we examine the application of electronic mar-ketplaces, populated by buying and selli...
Online feedback-based rating systems are gaining popularity. Dealing with unfair ratings in such sys...
If you ever buy thing online from an unknown seller, the seller’s rating information that is given t...
In multiagent e-markets, trust between interaction partners (buying agents and selling agents) is vi...
Part 3: Access Control, Trust and Identity ManagementInternational audienceOnline rating systems are...
Trust systems help users evaluate trustworthiness of partners, which support users to make decisions...
Unfair rating attacks to trust systems can affect the accuracy of trust evaluation when trust rating...
Online rating systems provide users with information to make decisions. However, these systems ma...
Ratings provided by advisors can help an advisee to make decisions, e.g., which seller to select in ...
In pervasive/ubiquitous computing environments, interacting users may evaluate their respective trus...
In electronic marketplaces populated by self-interested agents, buyer agents would benefit by modeli...
In trust systems, unfair rating attacks – where advisors provide ratings dishonestly – influence the...
In rating systems, users want to construct accurate opinions based on ratings. However, the accuracy...
research is within the area of artificial intelligence and multi-agent systems. More specifically, w...
In trust systems, unfair rating attacks — where advisors provide ratings dishonestly — influence the...
In this paper, we examine the application of electronic mar-ketplaces, populated by buying and selli...
Online feedback-based rating systems are gaining popularity. Dealing with unfair ratings in such sys...
If you ever buy thing online from an unknown seller, the seller’s rating information that is given t...
In multiagent e-markets, trust between interaction partners (buying agents and selling agents) is vi...
Part 3: Access Control, Trust and Identity ManagementInternational audienceOnline rating systems are...
Trust systems help users evaluate trustworthiness of partners, which support users to make decisions...
Unfair rating attacks to trust systems can affect the accuracy of trust evaluation when trust rating...
Online rating systems provide users with information to make decisions. However, these systems ma...
Ratings provided by advisors can help an advisee to make decisions, e.g., which seller to select in ...
In pervasive/ubiquitous computing environments, interacting users may evaluate their respective trus...
In electronic marketplaces populated by self-interested agents, buyer agents would benefit by modeli...
In trust systems, unfair rating attacks – where advisors provide ratings dishonestly – influence the...
In rating systems, users want to construct accurate opinions based on ratings. However, the accuracy...
research is within the area of artificial intelligence and multi-agent systems. More specifically, w...
In trust systems, unfair rating attacks — where advisors provide ratings dishonestly — influence the...
In this paper, we examine the application of electronic mar-ketplaces, populated by buying and selli...
Online feedback-based rating systems are gaining popularity. Dealing with unfair ratings in such sys...
If you ever buy thing online from an unknown seller, the seller’s rating information that is given t...