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  • 标题:J.UCS Special Issue: I-KNOW '02 Technology-Oriented Knowledge Management
  • 本地全文:下载
  • 作者:Klaus Tochtermann Hermann Maurer
  • 期刊名称:Journal of Universal Computer Science
  • 印刷版ISSN:0948-6968
  • 出版年度:2002
  • 卷号:8
  • 期号:6
  • 出版社:Graz University of Technology and Know-Center
  • 摘要:

    It is widely recognized that the transitions to an information society and a global knowledge economy will be the most important social and economic changes of the next decade. The global knowledge economy with its high innovation speed and an increasing demand of knowledge intensive products and services calls for new management tools and methods. Therefore, efficient management of knowledge has become imperative for almost all types of organizations.

    Knowledge management can be addressed from two different perspectives. The first perspective places the emphasis on information technologies as enabling technologies. The second perspective is more people-oriented as it focuses on people and organizations. The difference between these two perspectives is the level at which knowledge management is applied.

    The objective of technology-oriented knowledge management is to support knowledge workers at an operational level. That is, information technologies are used to provide the knowledge somebody needs to perform a specific task as well and as efficiently as possible. Often, this requires a careful and smooth integration of knowledge management tools with business process management tools.

    While the May issue of J.UCS addressed people-oriented knowledge management, this issue focuses on the role information technologies play in knowledge management. With this special issue we want to give the reader the possibility to get an overview of the leading edge technologies in knowledge management and how these technologies can be applied for knowledge management. To achieve this objective this issue covers the following thematic areas. Metadata and retrieval help users to find the knowledge they need to perform their tasks efficiently. Visualization techniques reduce the complexity of heterogeneous and complex knowledge spaces.

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