Development and evaluation of clustering techniques for finding people

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Abstract

Typically in a large organisation much expertise and knowledge is held informally within employees' own memories. When employees leave an organisation many documented links that go through that person are broken and no mechanism is usually available to overcome these broken links. This match making problem is related to the problem of finding potential work partners in a large and distributed organisation. This paper reports a comparative investigation into using standard information retrieval techniques to group employees together based on their webpages. This information can, hopefully, be subsequently used to redirect broken links to people who worked closely with a departed employee or used to highlight people, say indifferent departments, who work on similar topics. The paper reports the design and positive results of an experiment conducted at Risø National Laboratory comparing four different IR searching and clustering approaches using real users' web pages.
Original languageEnglish
Title of host publicationProceedings of the Third International on Practical Aspects of Knowledge Management
Place of PublicationBasel, Switzerland
Publication statusPublished - 2000

Publication series

NameCEUR Workshop Proceedings
PublisherCEUR-WS.org

Keywords

  • clustering
  • human computer interaction
  • knowledge management
  • information retrieval
  • mobile devices

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    Dunlop, M. D. (2000). Development and evaluation of clustering techniques for finding people. In Proceedings of the Third International on Practical Aspects of Knowledge Management (CEUR Workshop Proceedings)..