| 摘要: |
| 随着Web技术的不断更新与发展,知识图谱以其强大的语义处理能力与开放互联能力吸引了各行各业的关注。各行各业都在纷纷构建所属领域的知识图谱,如何从不同数据源抽取构建知识图谱所需概念,成为知识图谱构建的关键技术,概念抽取得越完整,所构建的知识图谱越全面,利用价值越高。本文对不同数据源抽取知识图谱概念进行阐述说明,以期引导学者选择合理的方法进行学术分析,提升知识图谱应用水平。 |
| 关键词: 领域知识图谱 概念抽取 数据源 |
| DOI：10.13657/j.cnki.gxkxyxb.20180320.004 |
| 投稿时间：2017-10-20修订日期：2017-11-20 |
| 基金项目:国家自然基金项目"蒙古语词汇语义网研究"(61363035)资助。 |
|
| A Survey of Knowledge Graph Concept Extraction Methods |
|
BIAN Huizhen, HA Si
|
| (Computer & Information Engineering College, Inner Mongolia Normal University, Hohhot, Inner Mongolia, 010022, China) |
| Abstract: |
| With the continuous updating and development of Web technology, the knowledge graph has been favored by various fields with its powerful semantic processing ability and open interconnection ability. The various walks of life are building the knowledge graphs in their own fields. How to extract required knowledge concepts from different data sources to build the knowledge graph becomes a key technology. The more complete the concept extraction, the more comprehensive the knowledge map, the higher the value of the use. This paper expounds the concept of the knowledge graph extracted from different data sources in order to guide scholars to choose a reasonable method for academic analysis and enhance the application level of the knowledge graph. |
| Key words: concept extraction domain knowledge graph data source |
