Interest-Matching Comparisons using CP-nets

Abstract

The formation of internet-based social networks has revived research on traditional social network models as well as interest-matching, or match-making, systems. In order to automate or augment the process of interest-matching, we follow the trend of qualitative decision theory by using qualitative preference information to represent a user's interests. In particular, a common form of preference statements for humans is used as the motivating factor in the formalization of ceteris paribus preference semantics. This type of preference information led to the development of conditional preference networks (CP-nets). This thesis presents a method for the comparison of CP-net preference orderings which allows one to determine a shared interest level between agents. Empirical results suggest that distance measure for preference orderings represented as CP-nets is an effective method for determining shared interest levels. Furthermore, it is shown that differences in the CP-net structure correspond to differences in the shared interest levels which are consistent with intuition. A generalized Kemeny and Snell axiomatic approach for distance measure of strict partial orderings is used as the foundation on which the interest-matching comparisons are based.