| 基于词内部模式的中文新词识别研究 |
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| 引用本文： | 廖祥文,林自芳,陈水利.基于词内部模式的中文新词识别研究[J].集美大学学报(自然科学版),2011(6):461-466. |
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| 作者姓名： | 廖祥文 林自芳 陈水利 |
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| 作者单位： | 福州大学数学与计算机科学学院;集美大学理学院; |
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| 基金项目： | 福建省自然科学基金资助项目(2010J05133); 福建省科技创新平台计划项目(2009J1007); 福州大学科技专项启动基金资助项目(2010-XQ-22) |
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| 摘 要： | 提出了一种基于支持向量机的中文新词识别算法.该算法结合新词内部模式以及词长等提出了基于词内部模式的改进字符位置似然概率,并综合新词的邻接类别等特征对新词进行识别.经过小说语料测试,实验结果表明：该算法的微F1值为0.583 3,宏F1值为0.775 7,分别比不考虑词内部模式的基准算法提高约63%和30%.
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| 关 键 词： | 中文新词 识别 词内部模式 字符位置似然概率 支持向量机 |
Research on Chinese New Word Identification Based on Inner Pattern of Word |
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| LIAO Xiang-wen,LIN Zi-fang,CHEN Shui-li.Research on Chinese New Word Identification Based on Inner Pattern of Word[J].the Editorial Board of Jimei University(Natural Science),2011(6):461-466. |
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| Authors: | LIAO Xiang-wen LIN Zi-fang CHEN Shui-li |
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| Institution: | LIAO Xiang-wen1,LIN Zi-fang1,CHEN Shui-li2(1.College of Mathematics and Computer Science,Fuzhou University,Fuzhou 350108,China,2.School of Science,Jimei University,Xiamen 361021,China) |
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| Abstract: | In this paper,a Chinese new word identification approach based on a SVM classifier was propose.The method first introduced improved independent word possibility based on the inner pattern of string and POS,and then combined accessor variety and frequency statistical features to identify Chinese new words.Experimental results showed that Micro F1 and Macro F1 of the proposed method were 0.583 3 and 0.775 7 respectively.Compared with the method not considening inner pattern of word,the performance of the pres... |
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| Keywords: | Chinese new word identification inner pattern of word independent word possibility SVM |
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