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Proceedings Paper

Study of item matching algorithm based on bipartite graph joint clustering for technology transaction platform
Author(s): Ming Zhu; Nana Huang; Cairong Yan
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Paper Abstract

For How to match supply items with demand items is the most important on technology transaction platform. A matching algorithm based on bipartite graph is proposed in this paper. Firstly, by abstracting characters the suppliers and demanders can be clustered into groups based on bipartite graph joint clustering method. Then, an incidence matrix between items in each group is built which is used to find the optimal matching relation. The simulate experiment results showed that the algorithm can return the item pairs of biggest transaction probability so as to make the Technology transaction platform efficient and profit.

Paper Details

Date Published: 13 March 2013
PDF: 6 pages
Proc. SPIE 8784, Fifth International Conference on Machine Vision (ICMV 2012): Algorithms, Pattern Recognition, and Basic Technologies, 87840K (13 March 2013); doi: 10.1117/12.2013809
Show Author Affiliations
Ming Zhu, Donghua Univ. (China)
Nana Huang, Donghua Univ. (China)
Cairong Yan, Donghua Univ. (China)


Published in SPIE Proceedings Vol. 8784:
Fifth International Conference on Machine Vision (ICMV 2012): Algorithms, Pattern Recognition, and Basic Technologies
Yulin Wang; Liansheng Tan; Jianhong Zhou, Editor(s)

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