摘要
随着医疗技术和生物科技的快速发展,生物领域的大数据急剧膨胀,数据的快速、有效检索成为了至关重要的问题。本文针对疾病本体及其相关数据的检索问题,提出了基于疾病本体的关联搜索算法。首先,根据多种医疗数据库中的原始数据,构建异构知识网络,之后,设计了在知识网络中进行关联搜索的算法,算法对节点与关键字之间的每条路径进行评分,并选取其中评分最高的路径作为该节点的最后得分,最终选取得分最高的若干个节点。结果表明,该算法有效地搜索出了与关键字关联度较大地数据。
With the rapid development of medical technology and biotechnology,the biological data has been expanded rapidly,so that the rapid and efficient retrieval of data has become a crucial issue.In this paper,an association search algorithm based on disease ontology is proposed for the retrieval of disease ontology and its related data.First,the paper builds heterogeneous knowledge network based on a variety of medical databases.After that,the paper designs the association search algorithm in the knowledge network.The algorithm scores each path between the node and the keyword,and selects the path with the highest score as the final score of the node.Finally,the paper selects nodes with highest scores as the search results.The results show that the algorithm is effective in searching for data with large correlation with keywords.
作者
梅祎
王亚东
MEI Yi;WANG Yadong(School of Computer Science and Technology,Harbin Institute of Technology,Harbin 150001,China)
出处
《智能计算机与应用》
2020年第1期233-236,共4页
Intelligent Computer and Applications
关键词
疾病本体
搜索
异构网络
disease ontology
search
heterogeneous network
