Key Relation Extraction from Biomedical Publications
Within the large body of biomedical knowledge,recent findings and discoveries are most often presented as research articles.Their number has been increasing sharply since the turn of the century,presenting ever-growing challenges for search and discovery of knowledge and information related to specific topics of interest,even with the help of advanced online search tools.This is especially true when the goal of a search is to find or discover key relations between important concepts or topic words.We have developed an innovative method for extracting key relations between concepts from abstracts of articles.The method focuses on relations between keywords or topic words in the articles.Early experiments with the method on PubMed publications have shown promising results in searching and discovering keywords and their relationships that are strongly related to the main topic of an article.
Data Mining Algorithms PubMed
Lan Huang Ye Wang Leiguang Gong Casimir Kulikowski Tian Bai
College of Computer Science and Technology,Jilin University,Changchun,Jilin,China;Key Lab of Symboli College of Computer Science and Technology,Jilin University,Changchun,Jilin,China College of Computer Science and Technology,Jilin University,Changchun,Jilin,China;Yantai Intelligent Department of Computer Science,Rutgers,The State University of New Jersey
国际会议
第十六届世界医药健康信息学大会((MEDINFO2017)、第二届世界医药健康信息学华语论坛(WCHIS 2017)、第15届全国医药信息学大会(CMIA 2017)
苏州
英文
873-877
2017-08-21（万方平台首次上网日期，不代表论文的发表时间）