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基于领域类别信息C-value的多词串自动抽取 被引量：7

Exploiting Domain Interdependence for Multi-Word Terms Extraction
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摘要 该本的多词串抽取是自然语言处理领域一项重要的研究内容。该文提出了一种多类别C-value(Multi-Class C-value)方法,利用多词串在不同领域的分布信息改善领域相关的多词串抽取的性能。在汽车、科技和旅行三个领域的数据上进行实验,评价多词串的准确率,在top-100级别上,较传统的C-value方法在三个领域中分别提高了12、12和13个百分点。实验结果验证了方法的有效性。 Automatic multi-word terms extraction attracts more and more attention in the research of natural language processing. This paper proposes a Multi-Class C-value method, which uses the distribution of multi-word terms in different domains, to improve the performance of multi-word terms extraction. In the experiment with the data of automobile, technology and trip, the precisions of top 100 multi-word terms are 12%, 12% and 13% higher than the clssical C-value method in three domains respectively.
作者 李超 王会珍 朱慕华 张俐 朱靖波
机构地区 东北大学自然语言处理实验室
出处 《中文信息学报》 CSCD 北大核心 2010年第1期94-98,共5页 Journal of Chinese Information Processing
基金 国家自然科学基金资助项目(60873091) 辽宁省自然科学基金资助项目(20072032) 沈阳市科学技术计划资助项目(1081235-1-00)
关键词 计算机应用 中文信息处理 多词串抽取 多类别C-value 领域信息 computer application Chinese information processing multi-word terms extractionl Multi-Class C- value domain information
分类号 TP391 [自动化与计算机技术—计算机应用技术]
  • 相关文献

参考文献9

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共引文献11

同被引文献98

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引证文献7

二级引证文献66

中文信息学报
2010年 第1期

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