基于作者权威值的论文价值预测算法

刘大有; 薛锐青; 齐红

doi:10.3724/SP.J.1004.2012.01654

基于作者权威值的论文价值预测算法

doi: 10.3724/SP.J.1004.2012.01654

1.
吉林大学计算机科学与技术学院长春 130012

详细信息

通讯作者:
齐红

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- 文章访问数: 1883
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- 被引次数: 0
出版历程
- 收稿日期: 2011-09-15
- 修回日期: 2012-01-10
- 刊出日期: 2012-10-20

The Paper Value Prediction Algorithm Based on the Author's Authority Value

1.
College of Mathematics, Jilin University, Changchun 130012

摘要

摘要: 论文引用网络是一个动态变化的网络,不断有新的论文加入引用网络中.传统的论文评价标准如引用次数、PageRank值等"终身评价标准"存在排挤新结点的问题,如何在海量论文中寻找有价值、被持续关注的论文,成为人们感兴趣的问题. Sayyadi提出了FutureRank算法,该算法通过预测论文未来"一段时间"的被引次数排名和PageRank值排名来达到这一目的.但FutureRank算法需提前计算PageRank值,要耗费大量运算时间.据此,我们尝试在不计算论文现有PageRank值的条件下,从论文的撰写者以及引用者的权威值的角度来预测论文未来的被引次数排名和PageRank值排名.实验结果表明,我们的算法与FutureRank相比,不但缩短了运算时间,而且提高了预测准确率.
- 引用网络 /
- 排名预测 /
- FutureRank /
- PageRank
Abstract: Citation network is a dynamic network and new papers are added to it every day. The traditional literature evaluation criteria like citations number and PageRank are unfair to the new node. How to retrieve the valuable papers of continuous concerns has become an interesting focus. To solve this problem, Hassan Sayyadi proposed the FutureRank algorithm, but it needs to calculate the PageRank value, which takes a lot of time. Accordingly, we proposed a paper value prediction algorithm without computing the PageRank value. We predict paper's rank of citations number and PageRank value in the future by writers' authority value and citer's authority value. Experimental results show that as compared with FutureRank, our algorithm not only shortens the computing time but also improves the forecast accuracy.
- Citation network /
- ranking prediction /
- FutureRank /
- PageRank

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参考文献(1)

[1]

Garfield E. Citation analysis as a tool in journal evaluation. Science, 1972, 178(4060): 471-479[2] Sayyadi H, Getoor L. Future rank: ranking scientific articles by predicting their future PageRank. In: Proceedings of the 9th SIAM International Conference on Data Mining. Sparks, NV: SIAM, 2009[3] Page L, Brin S, Motwani R, Winograd T. The PageRank Citation Ranking: Bringing Order to the Web. Technical Report. Stanford InfoLab, USA, 1998[4] Bollen J, Rodriguez M A, van de Sompel H. Journal status. Scientometrics, 2006, 69(3): 669-687[5] Chen P, Xie H, Maslov S, Redner S. Finding scientific gems with Google's PageRank algorithm. Journal of Informetrics, 2007, 1(1): 8-15[6] Ma N, Guan J C, Zhao Y. Bringing PageRank to the citation analysis. Information Processing Management, 2008, 44(2): 800-810[7] Bergstrom C T, West J D, Wiseman M A. The EigenfactorTMMetrics. Journal of Neuroscience, 2008, 28(45): 11433-11434[8] Kleinberg J M. Authoritative sources in a hyperlinked environment. Journal of the ACM, 1999, 46(5): 604-632[9] Berberich K, Vazirgiannis M, Weikum G. Time-aware authority ranking. Internet Mathematics, 2005, 2(3): 301-332[10] Dong A L, Chang Y, Zheng Z H, Mishne G, Bai J, Zhang R Q, Buchner K, Liao C Y, Diaz F. Towards recency ranking in web search. In: Proceedings of the 3rd ACM International Conference on Web search and data mining. New York, USA: ACM, 2010. 11-20[11] Walker D, Xie H F, Yan K K, Maslov S. Ranking scientific publications using a model of network traffic. Journal of Statistical Mechanics: Theory and Experiment, 2007, 2007(6): 06010[12] Yan E J, Ding Y. Weighted citation: an indicator of an article's prestige. Journal of the American Society for Information Science and Technology, 2010, 61(8): 1635-1643[13] Yan E J, Ding Y, Sugimoto C R. P-Rank: an indicator measuring prestige in heterogeneous scholarly networks. Journal of the American Society for Information Science and Technology, 2011, 62(3): 467-477[14] Yan E, Ding Y. Measuring scholarly impact in heterogeneous networks. Proceedings of the American Society for Information Science and Technology, 2010, 47(1): 1-7[15] Zhou D, Orshanskiy S A, Zha H Y, Yan K K. Coranking authors and documents in a heterogeneous network. In: Proceedings of the 7th IEEE International Conference on Data Mining. Omaha NE, USA: IEEE, 2007. 739-744

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