| 邹腊梅，龚向坚，肖芳，马淑萍.基于模拟退火算法与隐马尔可夫模型的Web信息抽取[J].南华大学学报(自然科学版),2011,25(1):70~74.[ZOU La-mei1,GONG Xiang-jian1,XIAO Fang2,MA Shu-ping1.Web Information Extraction Based on Simulated Annealing Algorithm and Hidden Markov Model[J].Journal of University of South China(Science and Technology),2011,25(1):70~74.] |
| 基于模拟退火算法与隐马尔可夫模型的Web信息抽取 |
| Web Information Extraction Based on Simulated Annealing Algorithm and Hidden Markov Model |
| 投稿时间：2010-12-20 |
| DOI： |
| 中文关键词: 模拟退火算法 隐马尔可夫模型 Web信息抽取 |
| 英文关键词:simulated annealing algorithm hidden Markov model Web information extraction |
| 基金项目:湖南省教育厅基金资助项目（O7C637） |
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| 摘要点击次数: 861 |
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| 中文摘要: |
| 典型隐马尔可夫模型对初始参数非常敏感，采用随机参数训练隐马尔可夫模型时常陷入局部最优，应用于Web信息抽取时效果不佳.文中提出基于模拟退火算法与隐马尔可夫模型的Web信息抽取算法.通过实验比较选择最佳的模拟退火算法参数，结合Baum-Welch算法优化隐马尔可夫模型并应用于Web信息抽取.实验结果表明新算法在信息抽取的精确率和召回率都有明显的提高. |
| 英文摘要: |
| Typical HMM is sensitive to the initial model parameters and often leads to sub-optimal when training it with random parameters.It is ineffective when extracting Web information with typical HMM.The artical proposes web information extraction algorithm based on SA and HMM.The algorithm chooses the best SA parameters by experiment and optimizes HMM combining Baum-Welch during the course of extracting Web information.Experimental results show that the new algorithm significantly improves the performance in precision and recall. |
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