A decision theoretic approach to combining information filters: An analytical and empirical evaluation

Yuval Elovici, Bracha Shapira, Paul B Kantor

Journal of the American Society for Information Science and Technology 57 (3 …, 2006

The outputs of several information filtering (IF) systems can be combined to improve filtering performance. In this article the authors propose and explore a framework based on the so‐called information structure (IS) model, which is frequently used in Information Economics, for combining the output of multiple IF systems according to each user’s preferences (profile). The combination seeks to maximize the expected payoff to that user. The authors show analytically that the proposed framework increases users expected payoff from the combined filtering output for any user preferences. An experiment using the TREC‐6 test collection confirms the theoretical findings.