多专长专家识别方法研究——以大数据领域为例

被引：10

作者：

刘晓豫

朱东华

汪雪锋

黄颖

机构：

[1] 北京理工大学管理与经济学院

来源：

图书情报工作 | 2018年 / 62卷 / 03期

关键词：

专家识别; 重叠K-means; 多专长专家; 大数据; TFIDF;

D O I：

10.13266/j.issn.0252-3116.2018.03.007

中图分类号：

TP311.13 [];

学科分类号：

1201 ;

摘要：

[目的 /意义]国家政府、大中型企业以及研究机构面对技术难题,如何找到合适的专家是迫切需要解决的问题。面对需要运用多学科知识来解决的综合性复杂难题,寻找到多专长专家显得尤为重要,寻找合适的方法识别出多专长专家是本研究的目的。[方法 /过程]利用专家所发表的学术论文数据,通过抽取专家有代表性的研究专长特征,基于TFIDF加权的重叠K-means聚类算法对专家进行重叠聚类划分,挖掘出专家的多个研究专长,进而识别出多专长专家。[结果 /结论]研究结果表明TFIDF加权的重叠K-means聚类算法在查准率、召回率和F值上有良好的表现,可以识别多专长专家。

引用

页码：55 / 63

页数：9

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