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Multi-facet classification of e-mails in a helpdesk scenario

  • Ingo Frommholz
    ,
  • Thomas Beckers
    ,
  • Ralf Bonning
  • University of Duisburg-Essen
Research Output:
Chapter in Book/Report/Conference proceeding
Conference contribution
 Peer-review

Open access

Abstract

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.

Publication Information

Output type

Research Output:
Chapter in Book/Report/Conference proceeding
Conference contribution
 Peer-review

Original language

English

Publication milestones

  • Published - 01/01/2009

Publication status

Published - 01/01/2009

Publisher

Gesellschaft für Informatik e.V., Germany

Publication IDs

  • handle.net: 10547/275694

Host publication title

nan

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