Medical ontology learning based on Web resources

摘要：

　　In order to deal with heterogeneous knowledge in the medical field, this paper proposes a method which can learn a heavy-weighted medical ontology based on medical glossaries and Web resources.Firstly, terms and taxonomic relations are extracted based on disease and drug glossaries and a lightweighted ontology is constructed; Secondly, non-taxonomic relations are automatically learned from Web resources with linguistic patterns, and the two ontologies (disease and drug) are expanded from light-weighted level towards heavy-weighted level;At last, the disease ontology and drug ontology are integrated to create a practical medical ontology.Experiment shows that this method can integrate and expand medical terms with taxonomic and different kinds of non-taxonomic relations.Our experiments show that the performance is promising.

关键词： non-taxonomic relations alias medical ontology heavy-weighted ontology

作者: Jun Peng Yam Du Ying Chen Ming Zhao Bei Pei

作者单位: College of Information and Electrical Engineering,China Agricultural University,Beijing 100083, Chin Key Lab of Information Network Security,Ministry of Public Security,Shanghai 200031, China

会议类型: 国际会议

会议名称: The 12th Web Information System and Application Conference第十二届全国Web信息系统及其应用学术会议(WISA2015)、全国第十次语义Web 与本体论学术研讨会(SWON2015)、全国第九次电子政务技术及应用学术研讨会(EGTA2015)

会议地点: 济南

会议语种:英文

页码: 116-119

在线出版日期: 2015-09-11（万方平台首次上网日期，不代表论文的发表时间）