"Many approaches for retrieving documents from electronic databases depend on the literal matching of words in a user's query to the keywords defining database objects. Since there is great diversity in the words people use to describe the same object, literal- or lexical- based methods can often retrieve irrelevant documents. Another approach to exploit the implicit higher-order structure in the association of terms with text objects is to compute the singular value decomposition (SVD) of large sparse term by text-object matrices. Latent Semantic Indexing (LSI) is a conceptual indexing method which employs the SVD to represent terms and objects by dominant singular subspaces so that user queries can be matched in a lower-rank semantic space. This paper considers a third, intermediate approach to facilitate the immediate detection of document (or term) clusters…."