作　　者： ;

机构地区： 中山大学

出　　处： 《数字图书馆论坛》 2018年第7期37-44,共8页

摘　　要： 为更好地评价学术会议等级,本文提出基于多指标的学术会议动态评价研究方法,收集人工智能领域2007—2014年的学术会议数据,共235个会议64 929篇论文的信息。通过7个指标与会议等级进行相关性分析,并应用Topsis模型对会议进行排名,得到每个会议的动态排名与综合分析结果。 In order to better evaluate the level of international academic conference, this paper proposes a research method of dynamic evaluation of academic conferences based on multiple indicators. Data of international academic conference is collected in the field of artificial intelligence from 2007 to 2014, which is including paper information of 64 929 papers in 235 conferences. The correlation analysis was carried out through 7 indicators and meeting grades, and the ranking of meetings was conducted by using Topsis, and the dynamic ranking and comprehensive analysis results of each meeting were obtained.

关 键 词： 会议评价 同侪声望 学术影响 TOPSIS模型

分 类 号： [G350]

领　　域： []