Automatic Domain Terminology Extraction Using Graph Mutual Reinforcement

摘要：

Information Extraction (IE) aims at mining knowledge from unstructured data. Terminology extraction is one of crucial subtasks in IE. In this pa per, we propose a novel approach of domain terminology extraction based on ranking, according to linkage of authors, papers and conferences in domain pro ceedings. Candidate terms are extracted by statistical methods and then ranked by the values of importance derived from mutual reinforcement result in the au thor-paper-conference graph. Furthermore, we integrate our approach with sev eral classical termhood-based methods including Cvalue and inverse document frequency. The presented approach does not require any training data, and can be extended to other domains. Experimental results show that our approach outperforms several competitive methods.

关键词： domain term terminology extraction graph mutual reinforcement

作者: Jingjing Kang Xiaoyong Du Tao Liu He Hu

作者单位: Key Labs of Data Engineering and Knowledge Engineering, Beijing 100872, China School of Information, Renmin University of China, Beijing 100872, China

会议类型: 国际会议

会议名称: 11th International Conference,WAIM 2010(第十一届网络时代管理国际会议)

会议地点: 九寨沟

会议语种:英文

页码: 656-667

在线出版日期: 2010-07-14（万方平台首次上网日期，不代表论文的发表时间）