Exploiting Context Information for Identification of Relevant Experts in Collaborative Workplace-Embedded E-Learning Environments

  • Robert Lokaiczyk
  • Eicke Godehardt
  • Andreas Faatz
  • Manuel Goertz
  • Andrea Kienle
  • Martin Wessner
  • Armin Ulbrich
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4753)


This work introduces an approach to discover collaboration partners and adequate advising experts in a workplace-embedded collaborative e-learning environment. Based on existing papers dealing with work task and user context modelling, we propose the following steps towards a successful collaboration initiation. In the beginning, the user’s current process task needs to be identified (1). Taking into account the knowledge about the current process, availability of experts as well as organizational and social distance, relevant experts regarding the actual work task of the learner are pre-selected by the environment (2). Depending on the pre-selection and users’ preferences, the potential collaboration partners are displayed in an expert list (3). That way, the learner is able to initiate beneficial collaborations, whose transcripts are used to enhance the existing knowledge base of learning documents (4).


Support Vector Machine Social Distance Work Task Knowledge Worker Task Prediction 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2007

Authors and Affiliations

  • Robert Lokaiczyk
    • 1
  • Eicke Godehardt
    • 2
  • Andreas Faatz
    • 1
  • Manuel Goertz
    • 1
  • Andrea Kienle
    • 3
  • Martin Wessner
    • 4
  • Armin Ulbrich
    • 5
  1. 1.SAP Research CEC Darmstadt, Bleichstr. 8, 64283 DarmstadtGermany
  2. 2.Fraunhofer IGD, Fraunhoferstr. 5, 64283 DarmstadtGermany
  3. 3.Fraunhofer IPSI, Dolivostr. 15, 64293 DarmstadtGermany
  4. 4.Ludwig-Maximilian-University, Leopoldstr. 13, 80802 MunichGermany
  5. 5.Know-Center, Inffeldgasse 21a, 8010 GrazAustria

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