首页 | 本学科首页   官方微博 | 高级检索  
     检索      

突发监测算法用于共词聚类分析的尝试
引用本文:王孝宁,崔雷,刘刚,黄亚明.突发监测算法用于共词聚类分析的尝试[J].图书情报工作,2009,53(12):104-120.
作者姓名:王孝宁  崔雷  刘刚  黄亚明
作者单位:中国医科大学信息管理与信息系统(医学)系
摘    要:Kleinberg算法能在不受外界因素影响的情况下及时发现未达到词频阀值要求但具有情报意义的词,用其计算突发词,并按突发权重排序,同时选择具有一定词频的突发词进行共词聚类分析,总结出当前医学信息学研究的热点领域。将分析结果与单一的高频词分析结果相比较,提出将突发词检测与高频词分析相结合以揭示信息科学的发展。

关 键 词:突发监测  共词分析  研究热点  医学信息学  
收稿时间:2008-12-09
修稿时间:2009-03-14

Attempt to Use Burst Detection in Co-Word Clustering Analysis
Wang Xiaoning,Cui Lei,Liu Gang,Huang Yaming.Attempt to Use Burst Detection in Co-Word Clustering Analysis[J].Library and Information Service,2009,53(12):104-120.
Authors:Wang Xiaoning  Cui Lei  Liu Gang  Huang Yaming
Institution:Department of Information Management and Information System (Medical), China Medical University
Abstract:Kleinberg’s burst detection algorithm can discover intelligence words are not reach requirement of frequency threshold in time with not affected by external factors. The paper uses Kleinberg’s burst detection algorithm to compute subject headings, and then sorts them by burst weigh. Also, it makes a co word clustering analysis of burst words with some frequency and summarizes hot topics of this field. Finally,the paper compares the results of analysis with results of high frequency words analysis and puts out that we should combine burst detection algorithm with high frequency words analysis to reveal the development of information science.
Keywords:burst detection  co-word analysis  hot topic  medical informatics
本文献已被 万方数据 等数据库收录!
点击此处可从《图书情报工作》浏览原始摘要信息
点击此处可从《图书情报工作》下载免费的PDF全文
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号