%T Bayes Optimal Metasearch: A Probabilistic Model for Combining the Results of Multiple Retrieval Systems
%A Javed A. Aslam
%A Mark Montague
%R Technical Report TR2000-382
%I Dartmouth College, Computer Science
%C Hanover, NH
%D December 2000
%U http://www.cs.dartmouth.edu/reports/TR2000-382.ps.Z
%X
 We introduce a new, probabilistic model for combining the outputs of
 an arbitrary number of query retrieval systems.  By gathering simple
 statistics on the average performance of a given set of query
 retrieval systems, we construct a Bayes optimal mechanism for
 combining the outputs of these systems.  Our construction yields a
 metasearch strategy whose empirical performance nearly always
 exceeds the performance of any of the constituent systems.  Our
 construction is also robust in the sense that if ``good'' and
 ``bad'' systems are combined, the performance of the composite is
 still on par with, or exceeds, that of the best constituent system.
 Finally, our model and theory provide theoretical and empirical
 avenues for the improvement of this metasearch strategy.
%Z
 Preliminary version appeared in SIGIR 2000.