%A Xia Tian %T Generating Hierarchical Paths of Chinese Text from Wikipedia %0 Journal Article %D 2016 %J Data Analysis and Knowledge Discovery %R 10.11925/infotech.1003-3513.2016.03.04 %P 25-32 %V 32 %N 3 %U {https://manu44.magtech.com.cn/Jwk_infotech_wk3/CN/abstract/article_4196.shtml} %8 2016-03-25 %X

[Objective] Generate hierarchical semantic paths of texts from Wikipedia. [Methods] We first establish article concept vector of Chinese texts from Wikipedia through explicit semantic analysis. And then, we mapped the vector to the category nodes of hierarchical-tree-like graph. Finally, we generated the hierarchical paths with the help of seed node information diffusion and top-down path selection, as well as optimization technology. [Results] The average relevance degree of the first generated hierarchical path was 54.10% on the test dataset, and the top 20 paths were sorted by relevance in the descending order. [Limitations] We did not analyze the effect of using different numbers of explicit concept vector to the quality of the generated path. [Conclusions] The hierarchical paths generated from Wikipedia can reflect the main semantic meaning of the given texts.