John O’Donovan, Barry Smyth, Vesile Evrim, Dennis McLeod
Buyers and sellers in online auctions are faced with the task of deciding who to entrust their business to based on a very limited amount of information. Current trust ratings on eBay average over 99 percent positive and are presented as a single number on a user profile. This paper presents a system capable of extracting valuable negative information from the wealth of feedback comments on eBay, computing personalized and feature-based trust and presenting this information graphically.
Subjects: 12. Machine Learning and Discovery; 1.10 Information Retrieval
Submitted: Oct 16, 2006