Learn More
In this paper, we propose a preference framework for information retrieval in which the user and the system administrator are enabled to express preference annotations on search keywords and document elements, respectively. Our framework is flexible and allows expressing preferences such as " A is infinitely more preferred than B, " which we capture by(More)
In this paper we propose a novel recommender system which enhances user-based collaborative filtering by using a trust-based social network. Our main idea is to use infinitesimal numbers and polynomials for capturing natural preferences in aggregating opinions of trusted users. We use these opinions to " help " users who are similar to an active user to(More)
  • 1