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| 基于知网和术语相关度的本体关系抽取研究* | |
| 引用本文： | 傅继彬,刘杰,贾可亮,毛金涛.基于知网和术语相关度的本体关系抽取研究*[J].现代图书情报技术,2008,24(9):36-40. |
| 作者姓名： | 傅继彬 刘杰 贾可亮 毛金涛 |
| 作者单位： | 1. 北京理工大学计算机科学技术学院,北京,100081 2. 首都师范大学信息工程学院,北京,100037 3. 山东经济学院信息管理学院,济南,250014 |
| 基金项目： | 教育部高等学校博士学科点专项科研基金 |
| 摘 要： | 提出一种基于知网和术语相关度的关系抽取方法。首先通过句法分析提取术语的上下文特征，结合自然语言特征和互信息的方法计算术语之间的相关度，然后使用术语的义原和动态角色作为关键词，在知网语义关系框架中定位关系，并为关系指定明确的语义标签。实验结果表明该方法具有较好的实用效果。 |
| 关 键 词： | 关系抽取 本体学习 知网 自然语言处理 |
| 收稿时间： | 2008-06-19 |
| 修稿时间： | 2008-07-07 |
Ontoloy Relationship Extraction Research Based on HowNet and Term Relevancy Degree |
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| Fu Jibin,Liu Jie,Jia Keliang,Mao Jintao.Ontoloy Relationship Extraction Research Based on HowNet and Term Relevancy Degree[J].New Technology of Library and Information Service,2008,24(9):36-40. | |
| Authors: | Fu Jibin Liu Jie Jia Keliang Mao Jintao |
| Institution: | (School of Computer Science and Technology, Beijing Institute of Technology, Beijing 100081, China) (School of Information Engineering, Capital Normal University, Beijing 100037, China) (School of Information Management, Shandong Economic University, Jinan 250014, China) |
| Abstract: | The paper proposes a relationship extraction method based on HowNet and term relevancy degree.Firstly syntax parsing tools are used to extract context feature of terms,and natural language feature and statistical mutual information measure are integrated to compute relevancy degree of terms,then dynamic role and sememe are used as key to seek the relationship in HowNet semantic relationship framework,and explicit semantic lable is designated to the relationship.Experimental results show that the approach is effective. |
| Keywords: | Relationship extraction Ontology learning HowNet NLP |
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