| 基于k-means聚类的无导词义消歧 |
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| 引用本文： | 陈浩,何婷婷,姬东鸿.基于k-means聚类的无导词义消歧[J].中文信息学报,2005,19(4):11-17. |
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| 作者姓名： | 陈浩 何婷婷 姬东鸿 |
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| 作者单位： | 1. 华中师范大学计算机科学系湖北武汉 430079 ; 2. 新加坡信息通讯研究所新加坡 119613 |
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| 基金项目： | 国家语委语言文字应用科研项目，湖北省自然科学基金 |
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| 摘 要： | 无导词义消歧避免了人工词义标注的巨大工作量,可以适应大规模的多义词消歧工作,具有广阔的应用前景。这篇文章提出了一种无导词义消歧的方法,该方法采用二阶context 构造上下文向量,使用k-means算法进行聚类,最后通过计算相似度来进行词义的排歧. 实验是在抽取术语的基础上进行的,在多个汉语高频多义词的两组测试中取得了平均准确率82167 %和80187 %的较好的效果。
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| 关 键 词： | 计算机应用 中文信息处理 词义消歧 HowNet 二阶context k-means 聚类 |
| 文章编号： | 1003-0077(2005)04-0010-07 |
| 修稿时间： | 2004年7月7日 |
An Unsupervised Approach to Word Sense Disambiguation Based on HowNet |
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| CHEN Hao,HE Ting-ting,JI Dong-hong.An Unsupervised Approach to Word Sense Disambiguation Based on HowNet[J].Journal of Chinese Information Processing,2005,19(4):11-17. |
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| Authors: | CHEN Hao HE Ting-ting JI Dong-hong |
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| Affiliation: | 1.Department of computer science , central china normal university , Wuhan , Hubei 430079 , China ;2.Institute for Infocomm Research , Heng Mui Keng Terrace , 21 , Singapore 119613 |
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| Abstract: | An unsupervised WSD(word sense disambiguation) can avoid big labor cost and it is possible to adjust to deal with large-scale ,so WSD has extensive applications in many fields. This paper presents an unsupervised approach which constructs context vector by means of second-order context, clustering by k-means and disambiguates by calculating the similarity. Our experiments are based on the extraction of term and average accuracy is 82.62% and 80.87% for 8 ambiguous words in open test by this method. |
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| Keywords: | HowNet |
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