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Automated knowledge discovery in advanced knowledge management

机译:高级知识管理中的自动化知识发现

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Purpose - To present approaches and some research results of various research areas contributing to knowledge discovery from different sources, different data forms, on different scale, and for different purpose. Design/methodology/approach - Contribute to knowledge management by applying knowledge discovery approaches to enable computer search for the relevant knowledge whereas the humans give just broad directions Findings - Knowledge discovery techniques proved to be very appropriate for many problems related to knowledge management Surprisingly, it is often the case that already relatively simple approaches provide valuable results. Research limitations/implications - Still there are many open problems and scalability issues that arise when dealing with real-world data and especially in the areas involving text and network analysis. Practical implications - Each problem should be handled with care, taking into account different aspects and selecting/extending the most appropriate available methods or developing some new approaches Originality/value - This paper provides an interesting collection of selected knowledge discovery methods applied in different context but all contributing in some way to knowledge management. Several of the reported approaches were developed in collaboration with the authors of the paper with especial emphases on their usability for practical problems involving knowledge management.
机译:目的-提出各种研究领域的方法和一些研究结果,这些方法和方法有助于从不同来源,不同数据形式,不同规模和不同目的中发现知识。设计/方法/方法-通过应用知识发现方法使计算机能够搜索相关知识,从而为知识管理做出了贡献,而人类只是给出了广泛的方向。结果-事实证明,知识发现技术非常适合与知识管理有关的许多问题。通常情况下,已经相对简单的方法可以提供有价值的结果。研究局限性/含义-在处理实际数据时,尤其是在涉及文本和网络分析的领域中,仍然存在许多未解决的问题和可伸缩性问题。实际意义-每个问题都应谨慎处理,要考虑到不同方面并选择/扩展最合适的可用方法或开发一些新方法原创性/价值-本文提供了一些有趣的选择知识发现方法,这些方法适用于不同背景,但是所有这些都以某种方式为知识管理做出了贡献。与本文作者合作开发了几种报告的方法,其中特别强调了它们在涉及知识管理的实际问题中的可用性。

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