XML document classification based on ELM
XML document classification based on ELM
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基于ELM的XML文档分类
DOI：
10.1016/j.neucom.2010.12.038
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发表时间：
2011-09
期刊：
影响因子：
6
通讯作者：
Gong Peizhen
中科院分区：
文献类型：
--
作者：
Wang Guoren;Zhao Xiangguo;Zhao Yuhai;Bi Xin;Gong Peizhen
In this paper, we describe an XML document classification framework based on extreme learning machine (ELM). On the basis of Structured Link Vector Model (SLVM), an optimized Reduced Structured Vector Space Model (RS-VSM) is proposed to incorporate structural information into feature vectors more efficiently and optimize the computation of document similarity. We apply ELM in the XML document classification to achieve good performance at extremely high speed compared with conventional learning machines (e.g., support vector machine). A voting-ELM algorithm is then proposed to improve the accuracy of ELM classifier. Revoting of Equal Votes (REV) method and Revoting of Confusing Classes (RCC) method are also proposed to postprocess the voting result of v-ELM and further improve the performance. The experiments conducted on real world classification problems demonstrate that the voting-ELM classifiers presented in this paper can achieve better performance than ELM algorithms with respect to precision, recall and F-measure.
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DOI：
10.1109/ijcnn.2008.4634028
发表时间：
2008-06
期刊：
2008 IEEE International Joint Conference on Neural Networks (IEEE World Congress on Computational Intelligence)
影响因子：
--
作者：
Hai-Jun Rong;G. Huang;Y. Ong
通讯作者：
Hai-Jun Rong;G. Huang;Y. Ong
影响因子：
6
作者：
Huang, Guang-Bin;Zhu, Qin-Yu;Siew, Chee-Kheong
通讯作者：
Siew, Chee-Kheong
DOI：
10.1109/iscis.2007.4456849
发表时间：
2007-11
期刊：
2007 22nd international symposium on computer and information sciences
影响因子：
--
作者：
Sherine Nagi Saleh;Egypt Yasser El-Sonbaty
通讯作者：
Sherine Nagi Saleh;Egypt Yasser El-Sonbaty
DOI：
10.1109/34.273716
发表时间：
1994-01-01
影响因子：
23.6
作者：
HO, TK;HULL, JJ;SRIHARI, SN
通讯作者：
SRIHARI, SN
DOI：
10.1145/347090.347164
发表时间：
2000-08
期刊：
--
影响因子：
--
作者：
Jeonghee Yi;Neel Sundaresan
通讯作者：
Jeonghee Yi;Neel Sundaresan