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A Component Clustering Algorithm Based on Semantic Similarity and Optimization

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4 Author(s)
Zhang Yingjun ; Inst. of Comput. Sci. & Technol., Taiyuan Univ. of Sci. & Technol., Taiyuan, China ; Ren Yaopeng ; Chen Lichao ; Xie Binhong

To overcome the subjective factors of faceted classification representation, the method combined the faceted classification with text retrieval is used to describe the components. Meanwhile, from the semantic view and combined optimization techniques, a component clustering algorithm based on semantic similarity and optimization is proposed. This algorithm can reduce the subjective factors of faceted classification, and further improve the efficiency and accuracy of component search. And compared with component clustering effect based on vector space model, the experiments prove that this component clustering algorithm based on semantic similarity and optimization is effective which can improve the result of component clustering and raise the clustering quality.

Published in:

Computational Aspects of Social Networks (CASoN), 2010 International Conference on

Date of Conference:

26-28 Sept. 2010