A New Approach of Automatic Entity Relation Extraction Combined Multimachine Learning

摘要：

Entity Relation Extraction is solved in this paper.Our approach is very different from previous approach;the Conditional Random Fields (CRFs)-based machine learning is combined with the Bootstrapping algorithm.Based on the Bootstrapping algorithm,seed words and seed patterns were used to build a learning program,which extracts more characteristic words using Scalar Clusters as the important feature of CRFs algorithm.These characteristic words have semantic similarity with seed words.Moreover,Combined the CRFs algorithm,ten features have been proposed for entity relation extraction in this paper,which includes Morphology,grammar and semantic feature.The system architecture used for entity relation extraction has been constructed.Experiment shows that the performance is promising.So it is useful to extract automatic entity relation.

作者: Zhang Suxiang Zhang Suxian

作者单位: Department of Electronic and Communication Engineering of North ChinaElectric Power University,07100 Health Vocational and Technical Colleges of Hebei University,071000,Baoding

会议类型: 国际会议

会议名称: 9th International Conference on Signal Processing(第九届国际信号处理学术会议)(ICSP08)

会议地点: 北京

会议语种:英文

在线出版日期: 2008-10-26（万方平台首次上网日期，不代表论文的发表时间）