We investigate the use of multiword query features to improve the effectiveness of text-retrieval systems that accept natural-language queries. A relevance feedback process is explained that expands an initial query with single and multiword features. The multiword features are modelled as a set of words appearing within windows of varying sizes. Our experimental results suggest that windows of larger span yield improvements in retrieval over windows of smaller span. This result gives rise to a query contraction process that prunes 25% of the features in an expanded query with no loss in retrieval effectiveness. 1 Introduction The following work investigates the representation for queries used in text-based information retrieval systems. The query representation described has applications in document filtering, routing, and clustering in addition to website searching. Our primary focus is the use of query features that represent concepts expressible in natural language by multiple word...