Topic-based heterogeneous rank

被引:48
|
作者
Amjad, Tehmina [1 ,2 ]
Ding, Ying [1 ,4 ]
Daud, Ali [2 ]
Xu, Jian [3 ]
Malic, Vincent [1 ]
机构
[1] Indiana Univ, Sch Lib & Informat Sci, Bloomington, IN 47401 USA
[2] Int Islamic Univ, Dept Comp Sci & Software Engn, Islamabad, Pakistan
[3] Sun Yat Sen Univ, Sch Informat Management, Guangzhou 510275, Guangdong, Peoples R China
[4] Tongji Univ, Lib, Shanghai 200092, Peoples R China
关键词
Topic-based rank; Topic sensitive ranking; Heterogeneous networks; Topic modeling; JOURNAL SELF-CITATION; RANDOM-WALK; PAGERANK; IMPACT; EIGENFACTOR; CENTRALITY; INDICATOR; AUTHORS; MACRO;
D O I
10.1007/s11192-015-1601-y
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
Topic-based ranking of authors, papers and journals can serve as a vital tool for identifying authorities of a given topic within a particular domain. Existing methods that measure topic-based scholarly output are limited to homogeneous networks. This study proposes a new informative metric called Topic-based Heterogeneous Rank (TH Rank) which measures the impact of a scholarly entity with respect to a given topic in a heterogeneous scholarly network containing authors, papers and journals. TH Rank calculates topic-dependent ranks for authors by considering the combined impact of the multiple factors which contribute to an author's level of prestige. Information retrieval serves as the test field and articles about information retrieval published between 1956 and 2014 were extracted from web of science. Initial results show that TH Rank can effectively identify the most prestigious authors, papers and journals related to a specific topic.
引用
收藏
页码:313 / 334
页数:22
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