Automatic detection of accommodation steps as an indicator of knowledge maturing

  • Authors:

  • Johannes Moskaliuk;Andreas Rath;Didier Devaurs;Nicolas Weber;Stefanie Lindstaedt;Joachim Kimmerle;Ulrike Cress

  • Affiliations:

  • University of Tuebingen, Germany, Konrad-Adenauer-Str. 40, 72072 Tuebingen, Germany;KnowCenter, Austria, Inffeldgasse 21a, A-8010 Graz, Austria;CNRS/LAAS and Université/ de Toulouse/UPS, INSA, INP, ISAE/LAAS/7 avenue du colonel Roche, F-31077 Toulouse, France;KnowCenter, Austria, Inffeldgasse 21a, A-8010 Graz, Austria;KnowCenter, Austria, Inffeldgasse 21a, A-8010 Graz, Austria;University of Tuebingen, Germany, Konrad-Adenauer-Str. 40, 72072 Tuebingen, Germany;Knowledge Media Research Center, Germany, Konrad-Adenauer-Str. 40, 72072 Tuebingen, Germany

  • Venue:
  • Interacting with Computers
  • Year:
  • 2011

Quantified Score

Hi-index 0.00

Visualization

Abstract

Jointly working on shared digital artifacts - such as wikis - is a well-tried method of developing knowledge collectively within a group or organization. Our assumption is that such knowledge maturing is an accommodation process that can be measured by taking the writing process itself into account. This paper describes the development of a tool that detects accommodation automatically with the help of machine learning algorithms. We applied a software framework for task detection to the automatic identification of accommodation processes within a wiki. To set up the learning algorithms and test its performance, we conducted an empirical study, in which participants had to contribute to a wiki and, at the same time, identify their own tasks. Two domain experts evaluated the participants' micro-tasks with regard to accommodation. We then applied an ontology-based task detection approach that identified accommodation with a rate of 79.12%. The potential use of our tool for measuring knowledge maturing online is discussed.