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Web信息抽取中基于神经网络的规则学习方法 被引量：1

An Approach of Rule Extraction Based on Artificial Neural Network in Web Information Extraction
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摘要 Web信息抽取是一个根据抽取的规则,从半结构化的网页文档中抽取相关数据,并将它们转化为结构化的数据的过程.其中抽取规则是信息抽取系统的基础,很多信息抽取规则学习方法已经被提出来.提出一种基于神经网络学习的规则抽取方法,可以通过学习训练样本形成较一般的信息抽取规则,并能够根据所产生的错误的实例自动调整权值,提高包装器的适应性.
作者 明廷波 左志宏 史永刚 林琳
机构地区 电子科技大学计算机学院
出处 《南京大学学报（自然科学版）》 CAS CSCD 北大核心 2005年第z1期1-6,共6页 Journal of Nanjing University（Natural Science）
关键词 WEB信息抽取 包装器 神经网络 规则抽取
分类号 TP391 [自动化与计算机技术—计算机应用技术]
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参考文献12

  • 1[1]Sahuguet A, Azavant F. Building intelligent web applications using lightweight wrappers. Data and Knowledge Engineering, 2001, 36(3):283～316.
  • 2[2]Muslea I, Minton S, Knoblock C. A hierarchical approach to wrapper induction. Proceedings of the Third International Conference on Autonomous Agents, 1999, 221～227.
  • 3[3]Gallant S I. Connection is the expert systems.Communications of the ACM, 1988,31 (2): 152～169.
  • 4[4]Saito K, Nakano R. Medical diagnostic expert system based on PDP model. Proceedings of the IEEE International Conference on Neural Networks.New York: IEEE Press, 1988,255～262.
  • 5[5]Fu L M. Rule learning by searching on adapted nets. Proceedings of the 9th National Conference on Artificial Intelligence. Anaheim, CA: AAAI Press, 1991. 590～ 595.
  • 6[6]Towell G G, Shavlik J W. Extracting refined rules from knowledge-based neural networks. Machine Learning, 1993,13(1) :71～ 101.
  • 7[7]Sestito S, Dillon T. Knowledge acquisition of conjunctive rules using multilayered neural networks.International Journal of Intelligent Systems, 1993,8(7) :779～805.
  • 8[8]Thrun S. Extracting rules from artificial neural networks with distributed representations. Tesauro G,Touretzky D, Leen T. Advances in Neural Information Processing Systems, Cambridge, MA: MIT Press, 1995.
  • 9[9]Craven M W, Shavlik J W. Extracting tree-structured representations of trained networks. Touretzky D, Moz-er M, Hassselmo M. Advances in Neural Information Processing Systems, Cambridge,MA: MIT Press, 1996,24～ 30.
  • 10[10]Setiono R. Extracting rules from neural networks by pruning and hidden-unit splitting. Neural Computation, 1997,9(1) :205～225.

二级参考文献1

  • 1Ham mar J，SIGMOD Record，1997年，26卷，2期，18页

共引文献46

同被引文献10

  • 1Leek T R. Information Extraction Using Hidden Mark-Models [ D]. San Diego: [s. n.], 1997.
  • 2LI Weiying, Yi Kechu, Hu Zheng. Introducing neural predictor to hidden Markov model for speech recognition [ C]//ICSLP. Canada: [s.n. ] ,1992.
  • 3Nelwamondo F V, Marwala T, Mahola U. Early Classifications of Bearing Faults Using Hidden Markov Models, Gaussian Mixture Models[J]. Mel-Frequency Cepstral Coefficients and Fractals International Journal of Innovative Computing, Information and Control,2006,2 (6) : 1281 - 1299.
  • 4Schenk J, Rigoll G. Novel Hybrid NN/HMM Modelling Techniques for On - line Handwriting Recognition [ D ]. Munchen : Institute for Human-Machine Communication Technische University Munchen ,2002.
  • 5Rabiner L R, Lee C H, Juang B H. HMM Clustering for Connected Word Recognition [ C ]//Proc. of IEEE ICASSP. [ s. l. ] : [ s. n. ] , 1989:405-408.
  • 6Freitag D, McCallum A K. Information extraction with HMM and Shrinkage[R]. [ s. l. ]: [ s. n. ] ,1999.
  • 7Freitag D, McCallum A. Information extraction with HMM structures learned by stochastic optimization [ C ]//Proceedings of the Eighteenth Conference on Artificial Intelligence. [s. l. ]:[s. n. ] ,2000:584-589.
  • 8Freitag D, McCallum A, Pereira F. Maximum Entropy Markov Models for Information Extraction and Segmentation [ C ]//7th International Conf. on Machine Learning. [ s. l. ] : [ s. n. ], 2000:591-598.
  • 9Scheffer T, Decomain C, Wrobel S. Active Hidden Markov Model for Information Extraction [ C ]//In Proceedings of the International Symposium on Intelligent Data Analysis. [ s. l. ] : [s. n. ] ,2001:309-318.
  • 10李帅,黄玺瑛,董家瑞.一种基于神经网络的特定文本信息提取方法[C]//第十届中国科协年会论文集(1).出版地不详:出版者不详,2008:420-424.

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南京大学学报（自然科学版）
2005年 第z1期

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