利用遗传算法确定医学文献的研究热点  

Application of Genetic Algorithm to Identify Hot Topics from Medical Literature

作　　者：张晗[1] 韩爽[1] 白星[2] 崔雷[1] 

机构地区：[1]中国医科大学信息管理与信息系统(医学)系,沈阳110001 [2]辉瑞制药有限公司,沈阳110014

出　　处：《现代图书情报技术》2011年第3期57-61,共5页New Technology of Library and Information Service

摘　　要：提取医学文献的主题词特征向量,检索文献在发表两年后的最新被引次数,以此作为热点文献的指标,利用遗传算法编程,优化提取出能表达热点文献内容的主题词组合。以肿瘤干细胞为测试对象,以词频分析所得的结果作为基准线,并请相关领域专家对两组结果进行评价比较,结果显示遗传算法所得到的结果优于词频分析。This paper firstly creates Medical Subject Headings （MESH） feature vector for medical literature, then searches for the latest cited times of each paper after published two years, which serves as the indicator for hot papers. Using a genetic program, a group of MeSH terms representing the content of hot papers are extracted. The method is tested on the topic of neoplastic stern cells,and the results from term frequency analysis are served as a baseline. The outputs of two methods are evaluated by domain experts,and the results show that genetic algorithm based method has a better performance than term frequency based method.

关 键 词：遗传算法 学科前沿 医学主题词 

分 类 号：TP18[自动化与计算机技术—控制理论与控制工程]