基于复杂关联网络的生物医学研究结构的挖掘

Complex associated network-based biomedical research structure mining

基于免费开放的Pub Med文献数据集,利用文献的知识发现,通过挖掘文献中隐含的关联,构建了生物医学实体关联演化网络。它能帮助科研人员形成新的科学假设,分析关联网络的拓扑特征,从系统层面上研究科学文献富集的知识结构、相关性与发展规律,为文献的知识发现引入新的视角与方法,提高知识发现的效率。

A biomedical entity association evolution network was constructed by mining the implicit associations in Pub Med-covered literature,which can help scientific researchers to form new scientific hypotheses,to analyze the topological features of associated network,to study the scientific literature-enriched knowledge structure,associations,development rules,to introduce new visual angles and methods for literature-based knowledge discovery,and to improve the knowledge discovery efficiency.