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    题名: Evaluating the impact power of authors via Bayesian estimation of authors' social connections
    作者: Tu, Y.-N.;Seng, Jia-Lang
    諶家蘭
    贡献者: 會計學系
    关键词: Bayesian estimations;Component;Impact power;Social connection;Topic detection;Estimation;Frequency estimation;Research;Social networking (online);Bayesian networks
    日期: 2011-07
    上传时间: 2015-10-08 17:51:08 (UTC+8)
    摘要: This study tries to detect the impact research topics from impact authors with their connections, that is, who have larger impact in the same research field. These topics are impact research topics the pursuit of which would be very valuable for researchers, especially for new scholars or for researchers who want to combine their original field with other new domains but who may not have enough background knowledge about the new field. Bayesian estimation in our model uses subjective data (published volume) as the prior distribution and objective data as the likelihood function (citation frequency) to predict the posterior distribution of the target which we called impact power. After finding the impact power of each paper or topic then filtering these papers and topics, we can find impact research topics or papers© 2011 IEEE.
    關聯: Proceedings - 2011 International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2011,論文編號 5992681,678-684
    数据类型: conference
    DOI 連結: http://dx.doi.org/10.1109/ASONAM.2011.17
    DOI: 10.1109/ASONAM.2011.17
    显示于类别:[會計學系] 會議論文

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