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題名 Evaluating the impact power of authors via Bayesian estimation of authors` social connections
作者 Tu, Y.-N.;Seng, Jia-Lang
諶家蘭
貢獻者 會計學系
關鍵詞 Bayesian estimations; Component; Impact power; Social connection; Topic detection; Estimation; Frequency estimation; Research; Social networking (online); Bayesian networks
日期 2011-07
上傳時間 8-十月-2015 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
資料類型 conference
DOI http://dx.doi.org/10.1109/ASONAM.2011.17
dc.contributor 會計學系
dc.creator (作者) Tu, Y.-N.;Seng, Jia-Lang
dc.creator (作者) 諶家蘭zh_TW
dc.date (日期) 2011-07
dc.date.accessioned 8-十月-2015 17:51:08 (UTC+8)-
dc.date.available 8-十月-2015 17:51:08 (UTC+8)-
dc.date.issued (上傳時間) 8-十月-2015 17:51:08 (UTC+8)-
dc.identifier.uri (URI) http://nccur.lib.nccu.edu.tw/handle/140.119/78913-
dc.description.abstract (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.
dc.format.extent 176 bytes-
dc.format.mimetype text/html-
dc.relation (關聯) Proceedings - 2011 International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2011,論文編號 5992681,678-684
dc.subject (關鍵詞) Bayesian estimations; Component; Impact power; Social connection; Topic detection; Estimation; Frequency estimation; Research; Social networking (online); Bayesian networks
dc.title (題名) Evaluating the impact power of authors via Bayesian estimation of authors` social connections
dc.type (資料類型) conferenceen
dc.identifier.doi (DOI) 10.1109/ASONAM.2011.17
dc.doi.uri (DOI) http://dx.doi.org/10.1109/ASONAM.2011.17