| 基于统计语义和结构特征的自动文摘 |
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| 引用本文： | 黄丽琼,何中市.基于统计语义和结构特征的自动文摘[J].广西师范大学学报(自然科学版),2006,24(4):187-190. |
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| 作者姓名： | 黄丽琼 何中市 |
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| 作者单位： | 1. 重庆大学,计算机学院,重庆,400044
2. 重庆大学,计算机学院,重庆,400044;重庆大学,语言认知及信息处理研究所,重庆,400044 |
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| 摘 要： | 在分析自动文摘现有方法优缺点的基础上,提出了一种基于统计、语义和结构特征的自动文摘方法。用这些特征构成句子向量表示,并用机器学习的方法对其进行训练得到器,从而把自动文摘转换为分类问题。实验表明,该方法具有较好的重合率。同时,为了解决文摘的冗余和不连贯缺点,进行了一系列的后期处理,提高了文摘的质量。
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| 关 键 词： | 机器学习 自动文摘 句子相似度 自然语言处理 |
| 文章编号： | 1001-6600（2006）04-0187-04 |
| 收稿时间： | 2006-05-31 |
| 修稿时间： | 2006年5月31日 |
Automatic Summarization Based on Statistic Semantic and Structural Features |
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| HUANG Li-qiong,HE Zhong-shi.Automatic Summarization Based on Statistic Semantic and Structural Features[J].Journal of Guangxi Normal University(Natural Science Edition),2006,24(4):187-190. |
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| Authors: | HUANG Li-qiong HE Zhong-shi |
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| Institution: | College of Computer Science ,Chongqing University ,Chongqing 400044 ,China |
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| Abstract: | This paper presents a new automatic summarization method based on statistic,semantic and structural features while the advantages and disadvantages are analyzed for the popular methods of automatic summarization.There are eight features used to form the feature vector for each sentence,and the summarizer is gained by machine learning algorithms,so automatic summarization is changed into classification task.The experiment results show that the method maintains higher precision.Meanwhile,the paper processes a series of post processing to overcome the shortcoming of redundancy and incoherence,and it improves largely the quality of summary. |
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| Keywords: | machine learning automatic summarization sentence similarity natural language processing |
| 本文献已被 CNKI 维普 万方数据 等数据库收录！ |
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