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題名 An Empirical Investigation of research productivity on text mining - in bibliometrics view
作者 Hou, O.C.L.;Hsu, H.;Yang, J.-M.
楊建民
貢獻者 資管系
日期 2010
上傳時間 21-五月-2015 15:32:50 (UTC+8)
摘要 As the improvement of computing power, texting mining becomes more focused than before. In order to realize the literature productivity of such territory, we analyze the literatures on SSCI database with subjects as "Text Mining". Applied the methodology of bibliometrics, we found several outcomes in this research. First, the distribution of frequency indexes of author`s productivity fulfills Lotka`s Law. Second, we also apply Price`s Square Root Law & Pareto Principle to check the result and found that are not compliance with both of these. Third, from the distribution of the number of paper published each year we conclude the topic of "Text Mining" is still in peak period but may achieve mature stage in the near future. Finally, 56.25% of authors only contribute 1 paper and 82.74% authors` outcomes are less or equal 3. Contrarily, there are 6 authors with over 10 published papers and the most productive one even owns 37 papers on SSCI database.
關聯 Journal of Next Generation Information Technology, Volume 1, Issue 3, Pages 29-35
資料類型 article
DOI http://dx.doi.org/10.4156/jnit.vol1.issue3.4
dc.contributor 資管系
dc.creator (作者) Hou, O.C.L.;Hsu, H.;Yang, J.-M.
dc.creator (作者) 楊建民zh_TW
dc.date (日期) 2010
dc.date.accessioned 21-五月-2015 15:32:50 (UTC+8)-
dc.date.available 21-五月-2015 15:32:50 (UTC+8)-
dc.date.issued (上傳時間) 21-五月-2015 15:32:50 (UTC+8)-
dc.identifier.uri (URI) http://nccur.lib.nccu.edu.tw/handle/140.119/75216-
dc.description.abstract (摘要) As the improvement of computing power, texting mining becomes more focused than before. In order to realize the literature productivity of such territory, we analyze the literatures on SSCI database with subjects as "Text Mining". Applied the methodology of bibliometrics, we found several outcomes in this research. First, the distribution of frequency indexes of author`s productivity fulfills Lotka`s Law. Second, we also apply Price`s Square Root Law & Pareto Principle to check the result and found that are not compliance with both of these. Third, from the distribution of the number of paper published each year we conclude the topic of "Text Mining" is still in peak period but may achieve mature stage in the near future. Finally, 56.25% of authors only contribute 1 paper and 82.74% authors` outcomes are less or equal 3. Contrarily, there are 6 authors with over 10 published papers and the most productive one even owns 37 papers on SSCI database.
dc.format.extent 176 bytes-
dc.format.mimetype text/html-
dc.relation (關聯) Journal of Next Generation Information Technology, Volume 1, Issue 3, Pages 29-35
dc.title (題名) An Empirical Investigation of research productivity on text mining - in bibliometrics view
dc.type (資料類型) articleen
dc.identifier.doi (DOI) 10.4156/jnit.vol1.issue3.4
dc.doi.uri (DOI) http://dx.doi.org/10.4156/jnit.vol1.issue3.4