Term clustering and syntactic phrase formation are methods for transforming natural language text. Both have had only mixed success as strategies for improving the quality of text representations for document retrieval. Since the strengths of these methods are complementary, we have explored combining them to produce superior representations. In this paper we discuss our implementation of a syntactic phrase generator, as well as our preliminary experiments with producing phrase clusters. These experiments show small improvements in retrieval effectiveness resulting from the use of phrase clusters, but it is clear that corpora much larger than standard information retrieval test collections will be required to thoroughly evaluate the use of this technique.

The impact of using phrases as content representation for documents and for queries has generally been accepted as a desirable feature in information retrieval systems because phrases are generally regarded as being more content-bearing than their constituent words. This has been borne by experiments in which the impact of phrases on retrieval performance has usually been found to be positive. However, most of the experimental results reported have derived phrases from documents and from queries in a fully automatic way. While this is acceptable for document indexing it is less acceptable for query formulation which is increasingly heading towards being an iterative process with users investing time in browsing the term space to choose appropriate search terms. In this paper we report a series of experiments in which two users, one experienced and the other a novice, formulate their queries by browsing the term space in advance of issuing a retrieval request. For these users we analyse...