Abstract
We develop a novel user-centric modeling technology, which can dynamically describe and update a person’s expertise profile. In an enterprise environment, the technology can enhance employees’ collaboration and productivity by assisting in finding experts, training employees, etc. Instead of using the traditional search methods, such as the keyword match, we propose to use relational and evolutionary graph models, which we call ExpertiseNet, to describe and find experts. These ExpertiseNets are used for mining, retrieval, and visualization. We conduct experiments by building ExpertiseNets for researchers from a research paper collection. The experiments demonstrate that expertise mining and matching are more efficiently achieved based on the proposed relational and evolutionary graph models.
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References
Becerra-Fernandez, I.: Searching for Experts with Expertise-Locator Knowledge Management Systems. In: ACL 2001 Workshop Human Language Technology and Knowledge Management, pp. 9–16. New York (2001)
Bull, S., Greer, J., McCalla, G., Kettel, L., Bowes, J.: User Modelling in I-Help: What, Why, When and How. In: Proc. of the 8th International Conference on User Modeling, Sonthofen, Germany, pp. 117–126 (July 2001)
Deerwester, S., Dumais, S.T., Furna, G.W., Landauer, T.K., Harshman, R.: Indexing by Latent Semantic Analysis. Journal of the American Society for Information Science 41(6), 391–407 (1990)
Henzinger, M.: Hyperlink Analysis on the Web. IEEE Internet Computing 5(1), 45–50 (2001)
Kleinberg, J.: Authoritative sources in a hyperlinked environment. In: Proc. 9th ACM-SIAM Symposium on Discrete Algorithms, pp. 604–632 (1998)
Liu, P., Curson, J., Dew, P.M.: Exploring RDF for Expertise Matching within an Organizational Memory. In: Proc. of the 14th International Conference on Advanced Information Systems Engineering, pp. 100–116 (2002)
Maron, M.E., Curry, S., Thompson, P.: An Inductive Search System: Theory, Design and Implementation. IEEE Transaction on Systems, Man and Cybernetics 16(1), 21–28 (1986)
McCallum, A.K., Nigam, K., Rennie, J., Seymore, K.: Automating the construction of internet portals with machine learning. Information Retrieval 3(2), 127–163 (2000)
Mockus, A., Herbsleb, J.D.: Expertise Browser: a quantitative approach to identifying expertise. In: Proc. of the 24th International Conference on Software Engineering, pp. 503–512 (2002)
Page, L., Brin, S., Motwani, R., Winograd, T.: The PageRank Citation Ranking: Bringing Order to the Web. Stanford Digital Libraries Working Paper (1998)
Resnick, P., Iacovou, N., Suchak, M., Bergstrom, P., Riedl, J.: Grouplens: An open architecture for collaborative filtering of netnews. In: Proc. of the ACM Conference on Computer Supported Cooperative Work, pp. 175–186 (1994)
Sebastiani, F.: Machine learning in automated text categorization. ACM Computing Surveys 34(1), 1–47 (2002)
Schapire, R.E., Singer, Y.: BoosTexter: A boosting-based system for text categorization. Machine Learning 39(2/3), 135–168 (2000)
Snijders, T.A.B.: Models for Longitudinal Network Data. In: Carrington, P., Scott, J., Wasserman, S. (eds.) Models and methods in social network analysis, Ch.11, Cambridge University Press, New York (2004) (in press, to appear)
Snijders, T.A.B.: Markov Chain Monte Carlo Estimation of Exponential Random Graph Models. Journal of Social Structure 3(2) (2002)
Staab, S.: Human language technologies for knowledge management. Intelligent Systems 16(6), 84–94 (2001)
Steeter, L.A., Lochbaum, K.E.: An Expert/Expert Locating System based on Automatic Representation of Semantic Structure. In: Proc. of the Fourth IEEE Conference on Artificial Intelligence Applications, San Diego, CA, pp. 345–349 (1988)
Wasserman, S., Faust, K., Iacobucci, D.: Social Network Analysis: Theory and Methods. Cambridge University Press, Cambridge (1995)
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Song, X., Tseng, B.L., Lin, CY., Sun, MT. (2005). ExpertiseNet: Relational and Evolutionary Expert Modeling. In: Ardissono, L., Brna, P., Mitrovic, A. (eds) User Modeling 2005. UM 2005. Lecture Notes in Computer Science(), vol 3538. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11527886_14
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DOI: https://doi.org/10.1007/11527886_14
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-27885-6
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