Study of item matching algorithm based on bipartite graph joint clustering for technology transaction platform

Ming Zhu; Nana Huang; Cairong Yan

doi:10.1117/12.2013809

13 March 2013 Study of item matching algorithm based on bipartite graph joint clustering for technology transaction platform

Ming Zhu, Nana Huang, Cairong Yan

Author Affiliations +

Proceedings Volume 8784, Fifth International Conference on Machine Vision (ICMV 2012): Algorithms, Pattern Recognition, and Basic Technologies; 87840K (2013) https://doi.org/10.1117/12.2013809
Event: Fifth International Conference on Machine Vision (ICMV 12), 2012, Wuhan, China

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.

Citation Download Citation

Ming Zhu, Nana Huang, and Cairong Yan "Study of item matching algorithm based on bipartite graph joint clustering for technology transaction platform", Proc. SPIE 8784, Fifth International Conference on Machine Vision (ICMV 2012): Algorithms, Pattern Recognition, and Basic Technologies, 87840K (13 March 2013); https://doi.org/10.1117/12.2013809

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