Title
Using jiminy for run-time user classification based on rating behaviour
Abstract
This paper describes an application of our prototype implementation of Jiminy, a scalable distributed architecture for providing participation incentives in online rating schemes. Jiminy is based on an incentive model where participants are explicitly rewarded for submitting ratings, and are debited when they query a participating reputation management system (RMS). Providing explicit incentives increases the quantity of ratings submitted and reduces their bias by removing implicit or hidden rewards, such as those gained through revenge or reciprocal ratings. To prevent participants from submitting arbitrary or dishonest feedback for the purpose of accumulating rewards, Jiminy halts rewards for participants who are deemed dishonest by its probabilistic honesty estimator. Using this estimator, Jiminy can also perform classification of users based on their rating behaviour, which can be further used as criteria for filtering the rating information that users obtain from the RMS. More background on the theoretical foundations of Jiminy can be found in [1], while [2] provides details on the system design, implementation and performance evaluation.
Year
DOI
Venue
2006
10.1007/11755593_35
iTrust
Keywords
Field
DocType
rating information,probabilistic honesty estimator,online rating scheme,explicit incentive,dishonest feedback,rating behaviour,system design,prototype implementation,reciprocal rating,run-time user classification,reputation management system,distributed architecture,management system
Reciprocal,Incentive,Computer science,Honesty,Filter (signal processing),Systems design,Artificial intelligence,Probabilistic logic,Machine learning,Reputation management,Distributed computing,Estimator
Conference
Volume
ISSN
ISBN
3986
0302-9743
3-540-34295-8
Citations 
PageRank 
References 
0
0.34
3
Authors
4
Name
Order
Citations
PageRank
Evangelos Kotsovinos136122.80
Petros Zerfos295967.88
Nischal M. Piratla311110.46
Niall Cameron491.08