XCLSC: Structure and content-based clustering of XML documents

Karima Bessine, A. Nehar, H. Cherroun, A. Moussaoui
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引用次数: 5

Abstract

This paper proposes a novel Clustering approach for XML documents that combines both their content and structure information using tree structural-content summaries in order to reduce the size of the document. This reduction has twofold purpose. First, it reduces the size of the XML tree by eliminating redundant nodes. Second, it gathers similaire content. The clustering is performed according to a similarity measure that takes into account the structure and the content between levels. Several experiments are performed to explore the effectiveness of using tree structural summaries and constrained content in the clustering process. Empirical analysis reveals that the designed clustering approach using content within structure and tree structural summaries gives a better solution for XML clustering while improving runtime. It is very suitable when we deal with big data sets.
XML文档的基于结构和内容的聚类
本文提出了一种新的XML文档聚类方法,该方法使用树形结构-内容摘要结合XML文档的内容和结构信息,以减小文档的大小。这种减少有双重目的。首先,它通过消除冗余节点来减小XML树的大小。第二,它收集相似的内容。聚类是根据考虑了层次之间的结构和内容的相似性度量来执行的。通过几个实验来探索在聚类过程中使用树结构摘要和约束内容的有效性。实证分析表明,所设计的使用结构内内容和树状结构摘要的聚类方法在提高运行时间的同时,为XML聚类提供了更好的解决方案。它非常适合我们处理大数据集。
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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