language: en

Learning to Retrieve Information

Brian Bartell
Encylopdia Britannica and Institute for Neural Computation Computer Science & Engineering University of California, San Diego
La Jolla, California 92093
Garrison W. Cottrell
Institute for Neural Computation Computer Science & Engineering University of California, San Diego
La Jolla, California 92093
Rik Belew
Institute for Neural Computation Computer Science & Engineering University of California, San Diego
La Jolla, California 92093

Abstract Information retrieval differs significantly from function approximation in that the goal is for the system to achieve the same ranking function of documents relative to queries as the user: the outputs of the system relative to one another must be in the proper order. We hypothesize that a particular rank-order statistic, Guttman's point alienation, is the proper objective function for such a system, and demonstrate its efficacy by using it to find the optimal combination of retrieval experts. In application to a commercial retrieval system, the combination performs 47% better than any single expert.

1 Introduction