The problem of finding your way through a relatively unknown collection of digital documents can be daunting. Such collections sometimes have few categories and little hierarchy, or they have so much hierarchy that valuable relations between documents can easily become obscured.We describe here how our work in the area of term-recognition and sentence-based summarization can be used to filter the document lists that we return from searches. We can thus remove or downgrade the ranking of some documents that have limited utility even though they may match many of the search terms fairly accurately. We also describe how we can use this same system to find documents that are closely related to a document of interest, thus continuing our work to provide tools for query-free searching.