Methods exist for constant-time clustering of corpus subsets selected
via Scatter/Gather browsing [Cutting et al., 1993].  In this paper we
expand on those techniques, giving an algorithm for almost-constant-time
clustering of arbitrary corpus subsets.  This algorithm is never
slower than clustering the document set from scratch, and for
medium-sized and large sets it is significantly faster.  This
algorithm is useful for clustering arbitrary subsets of large
corpora -- obtained, for instance, by a boolean search -- quickly
enough to be useful in an interactive setting.