基于传递闭包方法的非相关文献知识发现探索——以癌药物靶点为例  

A Tentative Study of Disjoint Literature Discovery Based on Transitive Closure——Take Cancer Drug Target for Example

作　　者：杨渊[1,2,3] 高柳滨[2] 

机构地区：[1]中国科学院国家科学图书馆,北京100190 [2]中国科学院上海药物研究所,上海201203 [3]中国科学院研究生院,北京100049

出　　处：《现代图书情报技术》2010年第12期52-57,共6页New Technology of Library and Information Service

摘　　要：根据非相关文献知识发现的原理和思想,尝试将离散数学中传递闭包的知识运用到知识发现中,以寻找药物靶点之间的潜在关联为例,证明运用传递闭包的方法进行非相关文献知识发现的合理性和有效性,并将原有的三步知识发现模式发展为多步传递知识发现模式,得到更多的潜在关联,并保证较高的查准率和查全率。Based on the principle of disjoint literature knowledge discovery,transitive closure in discrete mathematics is applied to find potential associations among drug targets,which confirms that transitive closure based disjoint literature knowledge discovery is achievable and effective.What’s more,the paper makes the original three-step model to multi-step knowledge discovery model,which can get more potential associations but ensure relative high precision and high recall at the same time.

关 键 词：传递闭包 WARSHALL算法 向量空间模型 药物靶点 非相关文献 知识发现 

分 类 号：G353[文化科学—情报学]