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基于语义关系的疾病知识提取系统 被引量：1

Disease Knowledge Extraction System Based on Semantic Relation
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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Sem Rep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Sem Rep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。 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 Sem Rep semantic output. Experimental results show that the precise of experimental result is 0.76 referring to OMIM and GHR online databases.
作者 吴晓芳 杨志豪 林鸿飞 王健
机构地区 大连理工大学计算机科学与技术学院
出处 《计算机工程》 CAS CSCD 北大核心 2015年第1期284-288,295,共6页 Computer Engineering
基金 国家自然科学基金资助项目(61070098 61272373 61340020) 中央高校基本科研业务费专项基金资助项目(DUT13JB09) 国家社会科学基金资助项目(08BTQ025)
关键词 知识提取 语义关系提取 显著信息提取算法 SEM Rep工具 语义输出 网络图可视化 knowledge extraction semantic relation extraction significant information extraction algorithm Sem Rep tool semantic output network diagram visualization
分类号 TP311 [自动化与计算机技术—计算机软件与理论]
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参考文献13

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二级参考文献32

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