A Novel Method for Transforming XML Documents to Time Series and Clustering Them Based on Delaunay Triangulation

• 作者: Narges Shafieian
• 来源期刊: 应用数学(英文)
• 学科: 工学
• 关键词: XML Mining Document CLUSTERING XML CLUSTERING Schema Matching Similarity Measures DELAUNAY TRIANGULATION Cluster
• 年，卷（期）: 2015,（6）
• 页码范围: 1076-1085
• 页数: 10页
• 分类号: TP39

摘要

Nowadays exchanging data in XML format become more popular and have widespread application because of simple maintenance and transferring nature of XML documents. So, accelerating search within such a document ensures search engine’s efficiency. In this paper, we propose a technique for detecting the similarity in the structure of XML documents;in the following, we would cluster this document with Delaunay Triangulation method. The technique is based on the idea of representing the structure of an XML document as a time series in which each occurrence of a tag corresponds to a given impulse. So we could use Discrete Fourier Transform as a simple method to analyze these signals in frequency domain and make similarity matrices through a kind of distance measurement, in order to group them into clusters. We exploited Delaunay Triangulation as a clustering method to cluster the d-dimension points of XML documents. The results show a significant efficiency and accuracy in front of common methods.