Abstract
Publishing at high-rank journals is a common objective to most researchers, and there’s a crucial need for a journal ranking system with universal recognition. This paper presents a quantitative approach to rank scientific journals. The approach, HR-PageRank, combines weighted PageRank according to author’s H-index, and relevance between citing and cited papers. The output of the proposed approach is compared against journal impact factor, H5-index, PageRank algorithm and China Computer Federation ranking list. The experiments of quantifying scholarly impact objectively are conducted in two real scholarly data sets: (1) Microsoft Academic Graph and (2) Digital Bibliography and Library Project. Our experimental results indicate that HR-PageRank algorithm outperforms the well-known PageRank algorithm in finding the influential journals according to Spearman’s rank correlation coefficient, discounted cumulated gain and the correlation C.
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