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 In text retrieval, the goal is to have the system retrieve documents that are relevant to a user's query. Unfortunately, relevance is difficult to determine a priori, and may differ across users. This suggests the proper approach is to use an adaptive system that learns what is relevant from user feedback. However, most adaptive systems in the neural network literature are...

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