| 基于HMM和小波神经网络混合模型的Web信息抽取 |
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| 引用本文： | 李少天,肖基毅,虞乐. 基于HMM和小波神经网络混合模型的Web信息抽取[J]. 微计算机信息, 2012, 0(5): 136-138 |
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| 作者姓名： | 李少天 肖基毅 虞乐 |
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| 作者单位： | 南华大学计算机科学与技术学院 |
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| 摘 要： | 提出一种将隐马尔科夫模型(HMM)和小波神经网络(WNN)相结合的混合模型应用于信息抽取。其首先将网页节点特征化,并依据网页内容建立不同的HMM,之后通过WNN调用相应的HMM用于信息抽取。HMM无法准确抽取的重要信息,利用WNN做辅助判别。实验证明,该混合模型可以提高Web信息抽取的精准度。
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| 关 键 词： | 信息抽取 隐马尔科夫模型(HMM) 小波神经网络(WNN) |
Web Information Extraction Based on a hybrid of HMM/WNN |
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| LI Shao-tian,XIAO Ji-yi,YU Le. Web Information Extraction Based on a hybrid of HMM/WNN[J]. Control & Automation, 2012, 0(5): 136-138 |
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| Authors: | LI Shao-tian XIAO Ji-yi YU Le |
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| Affiliation: | (School of Computer and Technology,University of South China,Hengyang Hunan 421001,China) |
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| Abstract: | A hybrid model was presented for information extraction by using the combined Hidden Markov Models(HMM) and Wavelet Neural Network (WNN).It first characterize the node of the web and establish different HMM according to the content of the web. Then appropriate HMM is selected by WNN for information extraction.As HMM can not extract important information accurately, WNN is used as an auxilary tool to do the discrimination. Experiments show that this hybrid model can improve the accuracy of Web information extraction. |
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| Keywords: | Information Extraction hidden markov model wavelet neural networks |
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