A user-oriented model for expert finding

  • Authors:

  • Elena Smirnova;Krisztian Balog

  • Affiliations:

  • INRIA Sophia Antipolis - Méditerranée, France;Department of Computer and Information Science, Norwegian University of Science and Technology, Norway and ISLA, University of Amsterdam, The Netherlands

  • Venue:
  • ECIR'11 Proceedings of the 33rd European conference on Advances in information retrieval
  • Year:
  • 2011

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Abstract

Expert finding addresses the problem of retrieving a ranked list of people who are knowledgeable on a given topic. Several models have been proposed to solve this task, but so far these have focused solely on returning the most knowledgeable people as experts on a particular topic. In this paper we argue that in a real-world organizational setting the notion of the "best expert" also depends on the individual user and her needs.We propose a user-oriented approach that balances two factors that influence the user's choice: time to contact an expert, and the knowledge value gained after. We use the distance between the user and an expert in a social network to estimate contact time, and consider various social graphs, based on organizational hierarchy, geographical location, and collaboration, as well as the combination of these. Using a realistic test set, created from interactions of employees with a university-wide expert search engine, we demonstrate substantial improvements over a state-of-the-art baseline on all retrieval measures.