Creating knowledge from heterogeneous data stove pipes

L. Sokol
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引用次数: 4

Abstract

The modern day challenges posed by terrorism and crime mean that we must make better use of the data we collect. We need to create a process that can transform different types of explicit and structured data into actionable knowledge. We need to be able to create unified infrastructure that will support a single query across all of the data sources. This unified infrastructure would allow us to integrate different collection stove pipes, including: text, structured data, images, faxes, audio, and video. To create this unified structure, we transform the collection stovepipes into sets of derived data that are integrated with structured data. Knowledge discovery tools are used over the entire set of collected data. This paper will present some of the components that we have been using to create knowledge infrastructures as well as the types of analysis required by our clients.
从异构数据中创建知识
恐怖主义和犯罪构成的现代挑战意味着我们必须更好地利用我们收集的数据。我们需要创建一个流程,可以将不同类型的明确和结构化数据转换为可操作的知识。我们需要能够创建统一的基础设施,以支持跨所有数据源的单个查询。这个统一的基础设施将允许我们集成不同的收集管道,包括:文本、结构化数据、图像、传真、音频和视频。为了创建这个统一的结构,我们将收集烟囱转换为与结构化数据集成的派生数据集。知识发现工具用于收集的整个数据集。本文将介绍一些我们用来创建知识基础结构的组件,以及我们的客户所需要的分析类型。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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