Staff Similarity Computation in Technology Innovation Team

Abstract:

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The main objective of this investigation is to explore new similarity algorithms of staff similarity in technology innovation team. First, this paper proposes the knowledge representation model of technology staff based on network, and the cliques after clustering according to network feature expresses the sub-fields. Second, from the view of knowledge contained in technology staff, this paper proposes the similarity algorithm based on VSM and the similarity algorithm based on sub-field. Finally, we use the staff classification of one technology innovation team as case study. The experiment results reveal that the similarity of the new methods is accurate than that of the old method, and the information obtained by the new methods is more than that obtained by the old method.

Info:

Periodical:

Advanced Materials Research (Volumes 204-210)

Edited by:

Helen Zhang, Gang Shen and David Jin

Pages:

1771-1774

DOI:

10.4028/www.scientific.net/AMR.204-210.1771

Citation:

W. Sun and Y. Yu, "Staff Similarity Computation in Technology Innovation Team", Advanced Materials Research, Vols. 204-210, pp. 1771-1774, 2011

Online since:

February 2011

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Price:

$35.00

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