Approximate Validity of XML Streaming Data

Huang Cheng, Li Jun, M. D. Rougemont
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Abstract

We present a SAX implementation of the statistical embedding associated with XML data, introduced in [1], [2], which allows to efficiently decide eps-validity to any DTD or Schema, for the Edit Distance with Moves. It associates a generalized k-gram to unranked labelled trees (with k = 1/epsiv) from which any regular property can be approximately decided. We show how to exactly compute the k-gram with a SAX implementation using a memory of size d, the depth of the tree, and an approximate k-gram with queues of size M = 2k and a global memory of size 2k in the worst-case. Experiments on large XML files from the XML benchmark project confirm the error analysis for various values of M.
XML流数据的近似有效性
我们提出了与XML数据相关的统计嵌入的SAX实现(在[1],[2]中介绍),它允许有效地确定任何DTD或模式的eps有效性,用于移动编辑距离。它将广义k-gram与未排序的标记树(k = 1/epsiv)联系起来,从中可以近似确定任何规则属性。我们将展示如何使用SAX实现精确地计算k-gram,使用大小为d的内存、树的深度,以及在最坏情况下具有大小为M = 2k的队列和大小为2k的全局内存的近似k-gram。在XML基准测试项目中的大型XML文件上的实验证实了M的各种值的误差分析。
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