Multi-facet Classification of E-mails in a Helpdesk Scenario

Helpdesks have to manage a huge amount of support requests which are usually submitted via e-mail. In order to be assigned to experts efficiently, incoming e-mails have to be classified w. r. t. several facets, in particular topic, support type and priority. It is desirable to perform these classifications automatically. We report on experiments using Support Vector Machines and k-Nearest-Neighbours, respectively, for the given multi-facet classification task. The challenge is to define 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.