  In this paper, we report on domain clustering in the ambit of an adaptive MT
architecture. A standard bottom-up hierarchical clustering algorithm has been
instantiated with five different distances, which have been compared, on an MT
benchmark built on 40 commercial domains, in terms of dendrograms, intrinsic
and extrinsic evaluations. The main outcome is that the most expensive distance
is also the only one able to allow the MT engine to guarantee good performance
even with few, but highly populated clusters of domains.
