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Expert Finder for Wikis

Finding experts is a relevant problem in large, distributed organizations, and automated solutions are needed. In this paper, we propose an approach for finding experts among Wiki authors, since Wikis have emerged as important collaboration and knowledge management tool in enterprizes.

By analyzing revision histories and by semantically mapping Wiki contributions to concepts defined in corporate domain ontologies we identify experts. We apply semantic similarity metrics in order to detect references to ontology topics not explicitly mentioned in the text. Furthermore, we use information from the revision history in order to assess the level of expertise and examine the collaborative peer-reviewing processes happening in Wiki systems in order to calculate a reputation score for each author, based on the author's contribution lifetime.

We evaluated our approach on the Eclipse project Wiki and conducted a survey with Eclipse project members to assess the quality of our expert finding approach. The results show that the approach yields accurate expertise information.


  • Ralph Schäfermeier, Adrian Paschke: Using Domain Ontologies for Finding Experts in Corporate Wikis. Proceedings of the 7th International Conference on Semantic Systems, I-Semantics ’11, pages 63–70, New York, NY, USA, 7-9 Sept. 2011. Download Paper External Link
  • Ralph Schäfermeier: Experten in Unternehmenswikis finden: Prototyp und Evaluierung. , Xinnovations 2010, Berlin, Germany, 19-21 Sept. 2010. Download Paper External Link
  • Ralph Schäfermeier: Experten mittels Wikis finden, In: Johann-Christoph Freytag, Robert Tolksdorf (Hrsg.): Tagungsband Xinnovations 2009, Berlin, 14.-16. September 2009. ISBN: 978-3-00-028902-6. (pdf, presentation)
  • Ralph Schäfermeier: Finden von Experten in Unternehmenswikis, Diploma Thesis, FU Berlin, 2009.
  • Velten Heyn: Expert-Recommender-System als Plugin für das Bug-Tracking-System Jira, Bachelor Thesis, FU Berlin
  • Harold Boley, Adrian Paschke: Expert Querying and Redirection with Rule Responder. FEWS 2007: 9-22


Expert Finder in Bug Tracking Systems

The expert recommender extension of the Jira bug tracking system semantically searches for similar tickets in Jira and recommends experts and links to existing organizational (Wiki) knowledge for each ticket. This helps to avoid redundant work and supports the search and collaboration with experts in the project management and maintenance phase based on the semantically enriched tickets in Jira.


  • Velten Heyn, Adrian Paschke: Semantic Jira - Semantic Expert Finder in the Bug Tracking Tool Jira, 9th International Workshop on Semantic Web Enabled Software Engineering (SWESE 2013), Berlin, Germany, 2013 (pdf)
  • Velten Heyn, Adrian Paschke: Semantic Jira , Technical Report TR-B-13-04, Freie Universität Berlin, Fachbereich Mathematik und Informatik, Berlin, Germany, 2013
  • Velten Heyn: Expert-Recommender-System als Plugin für das Bug-Tracking-System Jira, Bachelor Thesis, FU Berlin, 2013

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© 2008 FU Berlin | Feedback
This work has been partially supported by the  InnoProfile-Corporate Semantic Web project funded by the German Federal Ministry of Education and Research (BMBF) and the BMBF Innovation Initiative for the New German Länder - Entrepreneurial Regions.
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