This paper discusses a retrieval scheme for an information retrieval system in which the feedback from a number of users of the system about its performance (global feedback) is stored in the form of clusters called user-oriented clusters. The clusters are described by using the description of its constituent documents. The clusters and queries are represented as vectors and the measure of similarity between them is represented as the cosine of the angle between the two. The clusters are retrieved as per decreasing order of similarity with respect to a query. An important problem that arises in the context of cluster description is the significance of an index term assigned to documents. This problem, called term refinement problem, is formulated and solved. The experimental results of the proposed retrieval scheme are compared with those of the vector space model and the results obtained are encouraging.
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