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Document Clustering in Military Explicit Knowledge: A Study on Peacekeeping Documents

机译:军事明确知识中的文件聚类:维持和平文件的研究

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In Military domain, knowledge can also be categorized into explicit knowledge and tacit knowledge, where the explicit military knowledge can be any form of knowledge that can easily articulated, codified, accessed and stored into various media forms. Further, advanced computer technologies give a convenient platform for digitizing documents, producing web documents and electronic documents, including this explicit military knowledge (e.g. military peacekeeping documents). The main goal here is to discover useful knowledge from military peacekeeping documents. Yet, text mining is a powerful technique that is widely used for discovering useful patterns and knowledge specially in unstructured text documents. This paper describes Text Analytics of Unstructured Data (TAUD) framework for analyzing and discovering significant text patterns exist in the military text documents. The framework consists of three (3) components: (i) data collection (ii) document preprocessing and (iii) text analytics and visualization which are word cloud and document clustering using K-Means algorithm. The findings of this study allow the military commanders and training officers to understand and access the military knowledge which they had learnt and gathered during the training programs before they can be deployed into a peacekeeping mission.
机译:在军事领域,知识也可以分类为明确的知识和默契知识,其中明确的军事知识可以是任何形式的知识,可以容易地阐明,编纂,访问和存储到各种媒体形式中。此外,高级计算机技术为数字化文档提供了方便的平台,生产网络文件和电子文件,包括这种明确的军事知识(例如军事维持和行业文件)。这里的主要目标是从军事维持和行业文件中发现有用的知识。然而,文本挖掘是一种强大的技术,广泛用于在非结构化文本文档中发现有用的模式和知识。本文介绍了非结构化数据(Taud)框架的文本分析,用于分析和发现军事文本文件中存在重要的文本模式。该框架由三(3)个组件组成:(i)数据收集(ii)文件预处理和(iii)文本分析和可视化,它们是使用k-means算法的字云和文档聚类。本研究的调查结果允许军事指挥官和培训人员了解并获取他们在培训方案中学习和聚集在培训方案中的军事知识,然后才能部署到维持和平特派团。

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