Helpdesks have to manage a huge amount of
support requests which are usually submitted
via e-mail. In order to be assigned to experts
e ciently, incoming e-mails have to be classi-
ed w. r. t. several facets, in particular topic,
support type and priority. It is desirable to
perform these classi cations automatically.
We report on experiments using Support Vector
Machines and k-Nearest-Neighbours, respectively,
for the given multi-facet classi -
cation task. The challenge is to de ne suitable
features for each facet. Our results suggest
that improvements can be gained for all
facets, and they also reveal which features are
promising for a particular facet