DocumentCode :
3648386
Title :
A Generalized Stereotypical Trust Model
Author :
Hui Fang;Jie Zhang;Murat Sensoy;Nadia Magnenat Thalmann
Author_Institution :
Sch. of Comput. Eng., Nanyang Technol. Univ., Singapore, Singapore
fYear :
2012
fDate :
6/1/2012 12:00:00 AM
Firstpage :
698
Lastpage :
705
Abstract :
Stereotypical trust modeling can be adopted by a buyer to effectively evaluate trustworthiness of a seller who has little or no past experience in e-marketplaces. The buyer forms trust stereotypes based on her past experience with other sellers. However, when the buyer has limited past experience with sellers, the formed stereotypes cannot accurately reflect her trust evaluation towards sellers. To address this issue, we propose a novel generalized stereotypical trust model. Specifically, we first build a semantic ontology to represent hierarchical relationships among seller attribute values. We then propose a fuzzy semantic decision tree (FSDT) learning method to construct trust stereotypes that generalizes over seller non-nominal attributes by splitting their values in a fuzzy manner, and generalizes over nominal attributes by replacing their specific values with more general terms according to the ontology. Experimental results confirm that our proposed model can more accurately measure the trustworthiness of sellers in simulated e-marketplaces where buyers have limited experience with sellers.
Keywords :
"Semantics","Ontologies","Decision trees","Learning systems","Cognition","Computers","Asia"
Publisher :
ieee
Conference_Titel :
Trust, Security and Privacy in Computing and Communications (TrustCom), 2012 IEEE 11th International Conference on
Print_ISBN :
978-1-4673-2172-3
Type :
conf
DOI :
10.1109/TrustCom.2012.29
Filename :
6296038
Link To Document :
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