Mining web data for competency management

J. Zhu, A.L. Goncalves, V.S. Uren, E. Motta, R. Pacheco

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

We present CORDER (COmmunity Relation Discovery by named Entity Recognition) an un-supervised machine learning algorithm that exploits named entity recognition and co-occurrence data to associate individuals in an organization with their expertise and associates. We discuss the problems associated with evaluating unsupervised learners and report our initial evaluation experiments.
Original languageEnglish
Title of host publicationProceedings of the 2005 IEEE/WIC/ACM International Conference on Web Intelligence (WI'05)
EditorsAndrzej Skowron, Rakesh Agrawal, Michael Luck, Takahira Yamaguchi, Pierre Morizet-Mahoudeaux, Jiming Liu, Ning Zhong
Place of PublicationWashington, DC (US)
PublisherIEEE
Pages94-100
Number of pages7
ISBN (Print)0-7695-2415-X
DOIs
Publication statusPublished - 2005
Event2005 IEEE/WIC/ACM International Conference on Web Intelligence - Compiegne, France
Duration: 19 Sep 200522 Sep 2005

Conference

Conference2005 IEEE/WIC/ACM International Conference on Web Intelligence
Abbreviated titleWI'05
CountryFrance
CityCompiegne
Period19/09/0522/09/05

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  • Cite this

    Zhu, J., Goncalves, A. L., Uren, V. S., Motta, E., & Pacheco, R. (2005). Mining web data for competency management. In A. Skowron, R. Agrawal, M. Luck, T. Yamaguchi, P. Morizet-Mahoudeaux, J. Liu, & N. Zhong (Eds.), Proceedings of the 2005 IEEE/WIC/ACM International Conference on Web Intelligence (WI'05) (pp. 94-100). IEEE. https://doi.org/10.1109/WI.2005.99