| 利用数据挖掘扩充量词名词词典的方法 |
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| 引用本文： | 张辉,徐菁,陆汝占.利用数据挖掘扩充量词名词词典的方法[J].计算机工程,2003,29(13):92-94. |
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| 作者姓名： | 张辉 徐菁 陆汝占 |
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| 作者单位： | 上海交通大学计算机科学与工程系,上海,200030 |
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| 摘 要： | 研究名词与量词的关系对于自然语言处理有很大的帮助，目前用于自然语言处理用的量词名词词典是由人工方法实现的，并由人工进行维护，有更新慢、收藏词少等缺点。该文利用数据挖掘技术对大规模真实文本进行分析，挖掘量词与名词的深层关系，有效地实现了对人工量词名词词典的扩充。
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| 关 键 词： | 数据挖掘 互信息 关联规则挖掘 量词名词词典 |
| 文章编号： | 1000-3428(2003)13-0092-03 |
| 修稿时间： | 2002年7月29日 |
Method of Using Data Mining to Extend Quantifier-Noun Dictionary |
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| ZHANG Hui,XU Jing,LU Ruzhan.Method of Using Data Mining to Extend Quantifier-Noun Dictionary[J].Computer Engineering,2003,29(13):92-94. |
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| Authors: | ZHANG Hui XU Jing LU Ruzhan |
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| Abstract: | A Quantifier-nonu dictionary plays an important role in many natural language processing applications,such as part-of-speech tagging,syntax analysis and machine translation. Currently, the quantifier-nonu dictionary is constructed by linguists.It can not be updated frequently and many lexicon entries may not be available. In this paper, a data-mining approach based on large-scale corpus analysis is used to extend a quantifier-noun dictionary. The main purpose is to make a quantifier-nonu dictionary more applicable.Experimental results show the approach is effective and suitable. |
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| Keywords: | Data mining Mutual information Association rule mining Quantifier-noun dictionary |
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