Title :
ε-collusion-proof mechanism for the aggregation of unverifiable cluster labels
Author :
Winoto, Pinata ; Tang, Tiffany Y.
Author_Institution :
Dept. Comput. Eng., Konkuk Univ., Chungju, South Korea
Abstract :
In this paper we study the collusion-proof property of a mechanism that is proposed for solving classification/clustering aggregation among selfish agents who tend to lie about their correct clustering/classes during the aggregation process. The ground-truth of the class labels is unknown, yet the agents are interested in the majority choice. The mechanism is first studied in [1], which shows the feasibility of it to foster agents´ truth-telling behavior, but failed to address its collusion-proof property. In this paper we show that the proposed mechanism is indeed satisfying the collusion-proof property under some conditions. A further analysis based on the property of the participating agents is also provided here.
Keywords :
data mining; distributed databases; pattern classification; pattern clustering; software agents; aggregation process; classification-clustering aggregation; collusion-proof property; database marketing; distributed data mining; foster agent truth-telling behavior; selfish agent; Companies; Equations; Games; Mathematical model; Mechanical factors; Nash equilibrium;
Conference_Titel :
Data Mining and Intelligent Information Technology Applications (ICMiA), 2011 3rd International Conference on
Conference_Location :
Macao
Print_ISBN :
978-1-4673-0231-9
