Learning to Retrieve Information
Information retrieval diiers signiicantly 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 eecacy by using it to nd the optimal combination of retrieval experts. In application to a commercial retrieval system, the combination performs 47% better than any single expert.