| 基于领域中文文本的术语抽取方法研究 |
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| 引用本文： | 谷俊,王昊.基于领域中文文本的术语抽取方法研究[J].现代图书情报技术,2011(4). |
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| 作者姓名： | 谷俊 王昊 |
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| 作者单位： | 南京大学信息管理系;上海宝山钢铁股份有限公司; |
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| 摘 要： | 在ICTCLAS词典分词的基础上,利用串频最大匹配算法从中文专利文本中抽取候选术语,再利用TF-IDF算法得到相关特征项的权重,经过筛选后得到最终概念术语。最后,抽取部分样本数据进行实验,并对结果进行分析。
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| 关 键 词： | 本体 概念抽取 串频最大匹配 TF-IDF 中文分词 |
Study on Term Extraction on the Basis of Chinese Domain Texts |
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| Gu Jun, Wang Hao.Study on Term Extraction on the Basis of Chinese Domain Texts[J].New Technology of Library and Information Service,2011(4). |
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| Authors: | Gu Jun Wang Hao |
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| Institution: | Gu Jun1,2 Wang Hao11(Department of Information Management,Nanjing University,Nanjing 210093,China)2(Baoshan Iron and Steel Company Ltd.,Shanghai 201900,China) |
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| Abstract: | Based on the ICTCLAS dictionary segmentation,this paper proposes a method that extracts relevant concept terminology from the Chinese patent texts by maximum matching and frequency statistics,then computes the weights of the items by TF-IDF and gets the final concept terminology.Finally,it analyzes the results with the sample data extraction experiments. |
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| Keywords: | Ontology Concept extraction Maximum matching and frequency statistics TF-IDF Chinese word segmentation |
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