Exploiting metadata for ontology-based visual exploration of weakly structured text documents

C. Seeling, A. Becks
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引用次数: 10

Abstract

A large amount of strategically relevant business information is contained in unstructured texts. While information brokering approaches are used to contextualize such documents and to generate metadata, text mining is used to explore large document spaces. So far, little attention has been paid on a value-adding combination of these technologies. We show how metadata and documents can be complementarily represented and used interactively to support users in text corpus analysis. We present a text analysis portal which displays inter-document similarity by means of so-called document maps, complemented by a display of the domain ontology and metadata-based access methods.
利用元数据对弱结构文本文档进行基于本体的可视化探索
大量与战略相关的商业信息包含在非结构化文本中。虽然信息代理方法用于将此类文档置于上下文中并生成元数据,但文本挖掘用于探索大型文档空间。到目前为止,很少有人关注这些技术的增值组合。我们展示了元数据和文档如何互补地表示和交互地使用,以支持文本语料库分析中的用户。我们提出了一个文本分析门户,通过所谓的文档映射来显示文档间的相似性,并辅以领域本体和基于元数据的访问方法的显示。
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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