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

Authors:
Yuval Elovici;Bracha Shapira;Paul B. Kantor
Affiliations:
Department of Information Systems Engineering, Ben-Gurion University, Beer-Sheva, Israel;Department of Information Systems Engineering, Ben-Gurion University, Beer-Sheva, Israel;Department of Library and Information Science, School of Communication Information and Library Studies (SCILS), Rutgers University, 4 Huntington Street, New Brunswick, NJ 08901-1071
Venue:
Journal of the American Society for Information Science and Technology
Year:
2006

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Abstract

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. © 2006 Wiley Periodicals, Inc.