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Tree view self-organisation of web content

机译:网络内容的树状自组织

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When browsing a large set of unstructured documents, it is advantageous if the documents have been organised and presented in a way that makes navigation efficient, understanding underlying concepts easy and locating related information quickly. This paper proposes a new method termed Treeview self-organising maps (Treeview SOMs) for clustering and organising text documents by means of a series of independently and automatically created, hierarchical one-dimensional SOMs. The method generates a topological taxonomy tree for a set of unstructured text documents in terms of presentation and visualisation. The documents are organised in a hierarchy of dynamically generated and automatically validated topics extracted from the corpus of the documents. The results presented in a labelled tree view, clearly show underlying contents of the documents and can help browsing the document set more efficiently than those of previous work using SOMs or hierarchical clustering methods. A brief overview on general document clustering and a review on SOM-based document analysis methods are also provided together with a comparison among them.
机译:在浏览大量非结构化文档时,如果以一种使导航高效,易于理解基本概念并快速找到相关信息的方式组织和呈现文档,则将非常有利。本文提出了一种称为Treeview自组织映射(Treeview SOM)的新方法,该方法通过一系列独立且自动创建的层次化一维SOM来聚类和组织文本文档。该方法在表示和可视化方面为一组非结构化文本文档生成拓扑分类树。这些文档按照从文档语料库中提取的动态生成并自动验证的主题的层次结构进行组织。以标记的树状视图显示的结果可以清楚地显示文档的基础内容,并且可以比使用SOM或分层聚类方法的先前工作更有效地浏览文档集。还提供了有关常规文档聚类的简要概述,并对基于SOM的文档分析方法进行了回顾,并进行了比较。

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