Message analysis for the recommendation of contact persons within defined subject fields

Today, a firm's employees embody a significant source of knowledge, not only by documenting knowledge, but also by assisting other colleagues with problem solving. Due to decentralising or business networking aiming at cooperation among companies, the transparency within an enterprise as to which employees are experts in what field diminishes. The purpose of IT-systems for expert recommendation is to endow employees with easy access to experts within certain subject fields. This paper illustrates the Xpertfinder method developed at the Fraunhofer IPA that analyses explicit knowledge forms such as E-Mail- or Newsgroup messages of logged-in users for the preparation of expert profiles. Contrary to common systems Xpertfinder only uses those parts of a message entirely created by the sender. The Latent Semantic Indexing methodology is used in order to determine the subject of each message. With the aid of Bayesian Belief Networks analysis results are combined to evocative expert characteristics for anonymous display. Measures for the protection of personal data as well as future research fields are adressed