Information retrieval: A sequential learning process

The fundamental problem of information retrieval is how to decide, on the basis of clues, each of which is an imperfect indicator of docuemnt relevance, which documents to retrieve and the order in which to present them. The most satisfying conceptual approaches have been based on probabilistic decision theoretic models. However, those previously used make a decision about a single document at a time, and extend this to retreiv e multiple docuemnts by ignoring interdocument interaction. The purpose of the articles is to present decision‐theoretic models which intrinsically include the multiple retrieval case. In particular, we argue that information retrieval should be envisioned as a process, in which the information retrieval system responds to a request by presenting documents to the patron in a sequence, gathering feedback as the process proceeds, and using this information to modify future retrieval. A retrieval strategy that naturally results from this model is described. Two examples are examined in detail.