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直推式支持向量机在Web信息抽取中的应用研究 被引量：6

Web information extraction based on Transductive Support Vector Ma-chine
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摘要 直推式支持向量机是一种直接从已知样本出发对特定的未知样本进行识别的分类技术。在分析直推式支持向量机分类原理的基础上,提出一种基于直推式支持向量机的Web信息抽取方法,直接从分类的角度抽取Web信息。只需要提供少量标记样本就可以实现对大量未标注样本的分类标注,从而以分类的方式完成Web数据抽取任务。实验结果表明,使用这种方法进行Web信息抽取是有效性。 Transductive Support Vector Machines（TSVM） classify the new data vector based on the information only related to this data vector.This paper proposes a Web information extraction method based on TSVM and extract Web information with the classify angle.It needs far less tagged samples to carry out classify mark a lot of untagged samples and complete Web information extraction by classified way.The results show that TSVM can be used in Web information extraction.
作者 肖建鹏 张来顺 任星
机构地区 中国人民解放军信息工程大学电子技术学院
出处 《计算机工程与应用》 CSCD 北大核心 2009年第2期147-149,共3页 Computer Engineering and Applications
关键词 WEB信息抽取 分类学习 直推式支持向量机 Web information extraction classification learning Transductive Support Vector Machine（TSVM）
分类号 TP311 [自动化与计算机技术—计算机软件与理论]
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参考文献8

  • 1许建华,张学工.统计学理论基础[M].北京:电子工业出版社,2004.
  • 2Vapnik V.The nature of statistical learning theory[M].New York:Springer-Verlag,2000.
  • 3陈毅松,汪国平,董士海.基于支持向量机的渐进直推式分类学习算法[J].软件学报,2003,14(3):451-460. 被引量：88
  • 4Joachims T.Transductive inference for text classification using support vector machines[C]//Proceeding of the 16th International Conference on Machine Learning.San Francisco:Morgan Kanfmann,1999:200-209.
  • 5Thorsten J.Transductive inference for text classification using support vector machines[C]//Proc of International Conference on Machine Learning.San Francisco,CA,USA:Morgan Kaufmann,1999:200-209.
  • 6Nikola K,Shaoning P.Transductive support vector machines and applications in bioinformatics for promoter recognition,letters and reviews[J].Neural Information Processing,2004,3 (2):31-38.
  • 7Yu S P,Cai D,Wen J R,et al.Improving pseudo-relevance feedback in Web information retrieval using Web page segmentation[EB/OL].http://research.microsoft.com/research/pubs/view.aspx?type=Technical] 20Report&id=6322002.
  • 8李保利,陈玉忠,俞士汶.信息抽取研究综述[J].计算机工程与应用,2003,39(10):1-5. 被引量：178

二级参考文献37

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共引文献264

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引证文献6

二级引证文献28

计算机工程与应用
2009年 第2期

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