We present an incentive-based architecture for providing recommendations in a social network. We maintain a distinct reputation system for each individual and we rely on users to ...
Rajat Bhattacharjee, Ashish Goel, Konstantinos Kol...
We study protocols to enable one user (the principal) to make potentially profitable but risky interactions with another user (the agent), in the absence of direct trust between ...
There is significant experimental evidence that prediction markets are efficient mechanisms for aggregating information and are more accurate in forecasting events than tradition...
Pseudo relevance feedback (PRF), which has been widely applied in IR, aims to derive a distribution from the top n pseudo relevant documents D. However, these documents are often ...
With the sheer growth of online user data, it becomes challenging to develop preference learning algorithms that are sufficiently flexible in modeling but also affordable in com...
Kai Yu, Shenghuo Zhu, John D. Lafferty, Yihong Gon...