Analysis of the Relationship between Proper nouns in Large Scale Corpus
大规模语料库中专有名词之间的关系分析
基本信息
- 批准号:15500090
- 负责人:
- 金额:$ 2.11万
- 依托单位:
- 依托单位国家:日本
- 项目类别:Grant-in-Aid for Scientific Research (C)
- 财政年份:2003
- 资助国家:日本
- 起止时间:2003 至 2004
- 项目状态:已结题
- 来源:
- 关键词:
项目摘要
In the first year, we have developed computer cluster system from parts, and developed the specialized software package for frequency analysis. Though most of these works are combination of existing result, we have realized a powerful environment to analyze the corpus. In the second year, we have used the SVM to detect keywords from corpus. The input of SVM is the statistical values of many strings, and the SVM judges whether the string is keywords or not. Sine this method does not use any kind of dictionary, the identical program works for both Japanese and Chinese. It is very interesting and remarkable result that the keyword can be extracted without any kind of dictionaries. All we need are samples of keywords in each language. We have also applied our environment to analyze the decease name of medical information systems. The data in the system consists of 7 years of medical record. Without our environment, it would be very difficult to analyze the data and get the synonyms of decease names from the data.
在第一年,我们从零开始开发了计算机集群系统,并开发了专门的频率分析软件包。虽然这些工作大多是结合已有的成果,但我们已经实现了一个强大的环境来分析语料库。在第二年,我们使用支持向量机从语料库中检测关键词。支持向量机的输入是多个字符串的统计值,支持向量机判断该字符串是否为关键字。由于这种方法不使用任何类型的字典,相同的程序适用于日语和汉语。这是非常有趣和显着的结果,可以提取的关键字没有任何种类的字典。我们所需要的只是每种语言的关键字样本。我们也应用我们的环境来分析医疗资讯系统的死亡名称。系统中的数据由7年的病历组成。如果没有我们的环境,这将是非常困难的分析数据,并从数据中获得死者姓名的同义词。
项目成果
期刊论文数量(16)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
Japanese Multiword Extraction using SVM and Adaptation
使用 SVM 和适应进行日语多词提取
- DOI:
- 发表时间:2004
- 期刊:
- 影响因子:0
- 作者:T.Ogata;K.Terao;K.Umemura
- 通讯作者:K.Umemura
武田善行, 梅村恭司, 藤井 敦: "Webマイニング"共立出版. 197 (2004)
Yoshiyuki Takeda、Kyoji Umemura、Atsushi Fujii:“网络挖掘”Kyoritsu Shuppan 197 (2004)。
- DOI:
- 发表时间:
- 期刊:
- 影响因子:0
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