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題名 Emerging topics detection and measurement
作者 杜逸寧;諶家蘭
Tu, Yi-Ning; Seng, Jia-Lang
貢獻者 會計系
日期 2012-04
上傳時間 28-四月-2014 15:39:51 (UTC+8)
摘要 This research presents endeavors that seek to identify the emerging topics for researchers and pinpoint research intelligence via academic papers. This study selects huge volume of papers and shows that the topics covered by conference papers in a year often leads to similar topics covered by journal papers in the subsequent year which can help researchers decrease the plenty of time and effort to detect all the academic papers. After that, in order to detect the emerging research topics the study uses the Bayesian estimation approach to estimate the impact of the authors and publications may have on a topic and to discover candidate emerging topics by the combination of the impact authors and publications. Researchers can assess the potential of these candidate emerging topics. Although these recommended topics will decrease the range of the search space, these topics may be so popular that all of the impact authors and publications discuss it. The search space is still large. The measurement tools or indices are needed. But the current methods only focus on the frequency of subjects and ignore the novelty of subjects which is critical. The frequency study only focuses on one of them and is without considering the potential of the topics. Finally the research also develops the measurement tools which can assess the research potential of the emerging topics. The proposed novel method can improve the limitations of impact factor method proposed by ISI. Besides, the method uses the impact power of the authors and the publications to measure the impact power of a paper before it really is one in order to solve the limitations of Google scholar`s approach. We suggest that the topic-oriented thinking of the new methods can really help the researchers to solve the problems of searching valuable topics.
關聯 Advanced science letters, 9(1), 653-659
資料類型 article
DOI http://dx.doi.org/10.1166/asl.2012.2506
dc.contributor 會計系en_US
dc.creator (作者) 杜逸寧;諶家蘭zh_TW
dc.creator (作者) Tu, Yi-Ning; Seng, Jia-Lang-
dc.date (日期) 2012-04en_US
dc.date.accessioned 28-四月-2014 15:39:51 (UTC+8)-
dc.date.available 28-四月-2014 15:39:51 (UTC+8)-
dc.date.issued (上傳時間) 28-四月-2014 15:39:51 (UTC+8)-
dc.identifier.uri (URI) http://nccur.lib.nccu.edu.tw/handle/140.119/65640-
dc.description.abstract (摘要) This research presents endeavors that seek to identify the emerging topics for researchers and pinpoint research intelligence via academic papers. This study selects huge volume of papers and shows that the topics covered by conference papers in a year often leads to similar topics covered by journal papers in the subsequent year which can help researchers decrease the plenty of time and effort to detect all the academic papers. After that, in order to detect the emerging research topics the study uses the Bayesian estimation approach to estimate the impact of the authors and publications may have on a topic and to discover candidate emerging topics by the combination of the impact authors and publications. Researchers can assess the potential of these candidate emerging topics. Although these recommended topics will decrease the range of the search space, these topics may be so popular that all of the impact authors and publications discuss it. The search space is still large. The measurement tools or indices are needed. But the current methods only focus on the frequency of subjects and ignore the novelty of subjects which is critical. The frequency study only focuses on one of them and is without considering the potential of the topics. Finally the research also develops the measurement tools which can assess the research potential of the emerging topics. The proposed novel method can improve the limitations of impact factor method proposed by ISI. Besides, the method uses the impact power of the authors and the publications to measure the impact power of a paper before it really is one in order to solve the limitations of Google scholar`s approach. We suggest that the topic-oriented thinking of the new methods can really help the researchers to solve the problems of searching valuable topics.en_US
dc.format.extent 154 bytes-
dc.format.mimetype text/html-
dc.language.iso en_US-
dc.relation (關聯) Advanced science letters, 9(1), 653-659en_US
dc.title (題名) Emerging topics detection and measurementen_US
dc.type (資料類型) articleen
dc.identifier.doi (DOI) 10.1166/asl.2012.2506-
dc.doi.uri (DOI) http://dx.doi.org/10.1166/asl.2012.2506-