| Distant Supervision方法中对齐数据的聚类去噪 |
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| 引用本文： | 朱兆龙,欧阳丹彤,叶育鑫.Distant Supervision方法中对齐数据的聚类去噪[J].吉林大学学报(理学版),2014,52(2):280-284. |
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| 作者姓名： | 朱兆龙 欧阳丹彤 叶育鑫 |
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| 作者单位： | 吉林大学 计算机科学与技术学院, 符号计算与知识工程教育部重点实验室, 长春 130012 |
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| 基金项目： | 国家自然科学基金(批准号:61133011;41172294;61170092) |
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| 摘 要： | 基于聚类和寻找表达语义关系的句子模式, 提出一种基于聚类去噪的distant supervision方法, 解决了传统distant supervision方法在知识库和文本集对齐阶段会引入噪声数据的问题, 得到了一种改进的distant supervision方法. 实验结果表明, 该方法可有效提高关系抽取任务的准确率.
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| 关 键 词： | 关系抽取 聚类 distant supervision方法 去噪 |
| 收稿时间： | 2013-01-31 |
Clustering Based Denoising for Aligned Data of Distant Supervision |
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| ZHU Zhao long,OUYANG Dan tong,YE Yu xin.Clustering Based Denoising for Aligned Data of Distant Supervision[J].Journal of Jilin University: Sci Ed,2014,52(2):280-284. |
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| Authors: | ZHU Zhao long OUYANG Dan tong YE Yu xin |
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| Institution: | Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education,College of Computer Science and Technology, Jilin Unive
rsity, Changchun 130012, China |
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| Abstract: | A new clustering based denoising method was proposed, with the help of clustering and recognizing patterns of sentences that express a relationship, to reduce the noisy data that was introduced in the alignment step of traditional distant supervision method. The experimental results demonstrate that our approach can significantly improve the accuracy of relation extraction system. |
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| Keywords: | relation extraction clustering distant supervision method denoising |
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