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Knowledge Management And Data Mining: Emerging Business Intelligence Research Subspecialties

机译:知识管理和数据挖掘:新兴商业智能研究亚特色

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Over the past five decades, the area of decision support systems has made a significant progress toward becoming a solid academic discipline. A number of prior studies have been conducted to assess the extent of progress within these stages in the DSS area. Among them, a study of Eom [1] has provided biblio-metric evidence that the decision support system has made meaningful progress over the past four and a half decades (1969-2004). The primary data for this study were gathered from a total of 498 citing articles in the BI area over the past eight years (2005-2012). This study uses author cocitation analysis (ACA). ACA is a technique of bibliometrics that applies quantitative methods to various media of communication such as books, journals, conference proceedings, and so on. Indeed, the results of this study showed the substantial changes in the intellectual structure of BI research. First, many research subspecialties appeared in the previous investigations up to 2004 have disappeared. They are individual differences/user interfaces, model management, and evaluation research during the period of 1969-2004. Second, through this research, we also noticed that the group support systems and foundation research are weakening in terms of the number of researchers and therefore the substantiality of these research topics are diminishing. On the other hand, the focus of business intelligence research is shifting to knowledge management and data mining.
机译:在过去的五十年中,决策支持系统的领域对成为一个稳固的学科进行了重大进展。已经进行了许多先前的研究,以评估DSS区域中这些阶段内的进展程度。其中,EOM [1]的研究提供了学生公制的证据,即决策支持系统在过去的四年半(1969-2004)中取得了有意义的进展。这项研究的主要数据是在过去八年(2005 - 2012年)中共有498篇引用498篇引用。本研究使用作者Cocitation分析(ACA)。 ACA是一种对诸如书籍,期刊,会议程序等的各种通信媒体的定量方法的方法。实际上,该研究的结果表明BI研究智力结构的重大变化。首先,在以前的研究中出现了许多研究亚特色,高达2004年的研究已经消失。他们是1969年至2004年期间的个人差异/用户界面,模型管理和评估研究。其次,通过这项研究,我们还注意到,基团支持系统和基础研究在研究人员的数量方面正在削弱,因此这些研究主题的实质性正在减少。另一方面,商业智能研究的重点转向知识管理和数据挖掘。

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