Web-Based Reputation Management Systems: Problems and Suggested Solutions
Electronic Commerce Research
A reputation-based trust model for peer-to-peer ecommerce communities [Extended Abstract]
Proceedings of the 4th ACM conference on Electronic commerce
Personalizing Trust in Online Auctions
Proceedings of the 2006 conference on STAIRS 2006: Proceedings of the Third Starting AI Researchers' Symposium
Trust Is in the Eye of the Beholder
CSE '09 Proceedings of the 2009 International Conference on Computational Science and Engineering - Volume 03
The sound of silence: mining implicit feedbacks to compute reputation
WINE'06 Proceedings of the Second international conference on Internet and Network Economics
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Online auctions are among the most important e-commerce services. Unfortunately it is very difficult to assure trust in such customer-to-customer environment. Most auction sites utilize a very simple participation counts system for reputation rating. This feedback-based reputation systems do not differentiate between sellers who trade in luxury goods and those who sell worthless trinkets. A fraudster can easily gain reputation by selling hundreds of cheap books and then cheat while selling a few expensive TV sets which are not as good as described on item page. In this paper we present a novel trust management method called Electrostatic Force Method (EFM) which calculates Personal Subjective Trust instead of overall reputation value. The trust value depends on price and category of an item one wants to buy. In this method a seller could have high trust value for someone who wants to buy a book and at the same time this seller may not be trustworthy for someone who wants to buy a TV set. Furthermore our method can be applied in addition to the system currently used by eBay-like online auction sites because it does not require any additional information other than positive, negative or neutral feedback on transactions.