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    Please use this identifier to cite or link to this item: http://ir.lib.ncu.edu.tw/handle/987654321/51825


    Title: An evolutionary PageRank approach for journal ranking with expert judgements
    Authors: Chen,YL;Chen,XH
    Contributors: 資訊管理學系
    Keywords: PARTICLE SWARM OPTIMIZATION;IMPACT FACTOR;ACCELERATION COEFFICIENTS;CITATION ANALYSIS;SEARCH ENGINE;MANAGEMENT;ALGORITHM;SCHOLARS;QUALITY;MIS
    Date: 2011
    Issue Date: 2012-03-27 19:07:08 (UTC+8)
    Publisher: 國立中央大學
    Abstract: The journal ranking problem has drawn a great deal of attention from researchers in various fields due to its importance in the evaluation of academic performance. Most previous studies solved the problem with either a subjective approach, based on expert survey metrics, or an objective approach, based on citation-based metrics. Since both have their own advantages and disadvantages, and since they are usually complementary, this work proposes a brand new approach that integrates the two. In this work, we propose the Evolutionary PageRank algorithm, which first uses the PageRank algorithm to evaluate journal prestige and then uses the Multi-Objective Particle Swarm Optimization to balance citation analysis and expert opinion. Experiments evaluating ranking quality were carried out with citation records and experts' surveys to show the effectiveness of the proposed method. The results indicate that the proposed method can improve PageRank journal ranking results.
    Relation: JOURNAL OF INFORMATION SCIENCE
    Appears in Collections:[資訊管理學系] 期刊論文

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