  Let $H=(V,E)$ be an edge-weighted hypergraph of rank $r$. Kogan and
Krauthgamer extended Bencz\'{u}r and Karger's random sampling scheme for cut
sparsification from graphs to hypergraphs. The sampling requires an algorithm
for computing the approximate strengths of edges. In this note we extend the
algorithm for graphs to hypergraphs and describe a near-linear time algorithm
to compute approximate strengths of edges; we build on a sparsification result
for hypergraphs from our recent work. Combined with prior results we obtain
faster algorithms for finding $(1+\epsilon)$-approximate mincuts when the rank
of the hypergraph is small.
