Two Stage Semantic Relation Extraction
Ontology is applied to a real-world web intelligent question answering system in PC troubleshooting domain as an improvement, so semantic relations need to be extracted to construct ontology semi-automatically. The paper mainly pays attention to “product-trouble relation and “productattribute relation. A two stage semantic relation extraction method is proposed. In stage one, relation identification is executed to produce high-precision relations instance as the seed for next stage; stage two is the actual relation extraction process, the related terms which describe troubleshooting information and attribute information are extracted based on association rules, then the terms is clustered to find target semantic relation. The relation extraction integrated the advantage of pattern-based and clustering-based methods. The experimental results show it is superior to individual patternbased and clustering-based methods in precision and recall.
ontology learning semantic relation extraction two stage extraction
Jibin Fu Xiaozhong Fan Jintao Mao Xiaoming Liu
School of Computer Science & Technology Beijing Institute of Technology Beijing, China
国际会议
2009 Ninth International Conference on Hybrid Intelligent Systems(第九届混合智能系统国际会议 HIS 2009)
沈阳
英文
1-5
2009-08-12（万方平台首次上网日期，不代表论文的发表时间）