Mining XML Document Based on Structure

M. G. Duaimi, Yasir Abd Alhamed
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Abstract

With the growing number of XML documents on the Web it becomes essential to effectively organize these XML documents in order to retrieve useful information from them. A possible solution is to apply clustering on the XML documents to discover knowledge that promotes effective data management, information retrieval and query processing. This paper presents a framework for clustering XML documents by structure. Modelling the XML documents as rooted ordered labeled trees, we study the usage of structural distance metrics in hierarchical clustering algorithms to detect groups of structurally similar XML documents. We suggest the usage of structural summaries for trees to improve the performance of the distance calculation and at the same time to maintain or even improve its quality.
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基于结构的XML文档挖掘
随着Web上XML文档数量的增长,有效地组织这些XML文档以便从中检索有用的信息变得至关重要。一种可能的解决方案是在XML文档上应用聚类来发现知识,从而促进有效的数据管理、信息检索和查询处理。本文提出了一个基于结构的XML文档聚类框架。将XML文档建模为有根有序的标记树,研究了在层次聚类算法中使用结构距离度量来检测结构相似的XML文档组。我们建议使用树的结构摘要来提高距离计算的性能,同时保持甚至提高距离计算的质量。
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