Title
Jiminy: a scalable incentive-based architecture for improving rating quality
Abstract
In this paper we present the design, implementation, and evaluation of Jiminy: a framework for explicitly rewarding users who participate in reputation management systems by submitting ratings. To defend against participants who submit random or malicious ratings in order to accumulate rewards, Jiminy facilitates a probabilistic mechanism to detect dishonesty and halt rewards accordingly. Jiminy's reward model and honesty detection algorithm are presented and its cluster-based implementation is described. The proposed framework is evaluated using a large sample of real-world user ratings in order to demonstrate its effectiveness. Jiminy's performance and scalability are analysed through experimental evaluation. The system is shown to scale linearly with the on-demand addition of slave machines to the Jiminy cluster, allowing it to successfully process large problem spaces.
Year
DOI
Venue
2006
10.1007/11755593_17
iTrust
Keywords
Field
DocType
rating quality,probabilistic mechanism,jiminy cluster,on-demand addition,proposed framework,large sample,experimental evaluation,cluster-based implementation,large problem space,malicious rating,honesty detection algorithm,scalable incentive-based architecture,management system
Dishonesty,Architecture,Reputation system,Incentive,Computer science,Honesty,Probabilistic logic,Reputation management,Distributed computing,Scalability
Conference
Volume
ISSN
ISBN
3986
0302-9743
3-540-34295-8
Citations 
PageRank 
References 
9
0.74
15
Authors
5
Name
Order
Citations
PageRank
Evangelos Kotsovinos136122.80
Petros Zerfos295967.88
Nischal M. Piratla311110.46
Niall Cameron491.08
Sachin Agarwal514516.54