摘要： 在生物医学领域,通过知识提取过程从海量的生物医学文献中提取疾病、基因和药物之间的关系并可视化显示,可以为临床医学实验提供有效的假设检验,推动生物医学科技的发展。为此,提出一种基于语义关系的以疾病为中心的疾病、基因和药物间的知识提取系统。利用SemRep得到特定主题Medline文献的语义输出,通过显著信息提取算法提取SemRep的语义输出关系。对照OMIM和GHR在线数据库进行评估,实验结果显示该显著信息提取系统的准确率可达0.76。
关键词:
知识提取,
语义关系提取,
显著信息提取算法,
SemRep工具,
语义输出,
网络图可视化
Abstract: In the biomedical field,knowledge summarization can greatly promote the innovation of biomedical science and technology.Dynamic summarization can provide novel clinical experimental hypothesis by extracting the links among diseases,genes,drugs from the mass of biomedical literature and visualizing it.This paper presents a system which summarizes the salient relations by the salient extraction algorithm using the specific subject Medline corpus by SemRep semantic output.Experimental results show that the precise of experimental result is 0.76 referring to OMIM and GHR online databases.
Key words:
knowledge extraction,
semantic relation extraction,
significant information extraction algorithm,
SemRep tool,
semantic output,
network diagram visualization
中图分类号:
吴晓芳,杨志豪,林鸿飞,王健. 基于语义关系的疾病知识提取系统[J]. 计算机工程, 2015, 41(1): 284-288.
WU Xiaofang,YANG Zhihao,LIN Hongfei,WANG Jian. Disease Knowledge Extraction System Based on Semantic Relation[J]. Computer Engineering, 2015, 41(1): 284-288.