会议专题

A component clustering algorithm based on semantic similarity and optimization

In overcome die subjective factors of faceted classification representation, the method combined die faceted classification frith 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.

faceted classification full-text retrieval semantic similarity clustering optimization component clustering

Zhang Yingjun Ren Yaopeng Chen Lichao Xie Bin hong

Taiyuan University of Science and Technology Institute of Computer Science and Technology Taiyuan Ch Taiyuan University of Science and Technology Institute of Computer Science and Technology Taiyuan Ch

国际会议

International Conference on Computational Aspects of Social Networks(国际社会网络计算会议 CASoN 2010)

太原

英文

53-57

2010-09-26(万方平台首次上网日期,不代表论文的发表时间)