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首页> 外文会议>International Conference on Conceptual Modeling; 20061106-09; Tucson,AZ(US) >OXONE: A Scalable Solution for Detecting Superior Quality Deltas on Ordered Large XML Documents
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OXONE: A Scalable Solution for Detecting Superior Quality Deltas on Ordered Large XML Documents

机译：OXONE：一种可伸缩的解决方案，用于在已订购的大型XML文档上检测卓越的质量增量

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摘要

Recently, a number of relational-based approaches for detecting the changes to XML data have been proposed to address the scalability problem of main memory-based approaches (e.g., X-Diff, XyDiff). These approaches store the XML documents in the relational database and issue SQL queries (whenever appropriate) to detect the changes. In this paper, we propose a relational-based ordered XML change detection technique (called OXONE) that uses a schema-conscious approach as the underlying storage strategy for XML data. Previous efforts have focused on detecting changes to ordered XML in an schema-oblivious storage environment. Although the schema-oblivious approach produces better result quality compared to XyDiff (a main memory-based ordered XML change detection approach), its performance degrade with increase in data size and is slower than XyDiff for smaller data set. We propose a technique to overcome these limitations. Our experimental results show that OXONE is up to 22 times faster and more scalable than the relational-based schema-oblivious approach. The performances of OXONE and XyDiff (C version) are comparable. However, more importantly, our approach is more scalable compared to XyDiff for larger datasets and has much superior the result quality of deltas than XyDiff.
机译：最近，已经提出了许多用于检测XML数据变化的基于关系的方法，以解决基于主存储器的方法（例如X-Diff，XyDiff）的可伸缩性问题。这些方法将XML文档存储在关系数据库中，并发出SQL查询（如果适用）以检测更改。在本文中，我们提出了一种基于关系的有序XML更改检测技术（称为OXONE），该技术使用模式意识方法作为XML数据的基础存储策略。先前的工作集中在检测模式无关的存储环境中对有序XML的更改。尽管与XyDiff（基于主内存的有序XML更改检测方法）相比，模式无关的方法产生的结果质量更好，但是其性能随着数据大小的增加而降低，并且对于较小的数据集，其性能比XyDiff慢。我们提出了一种克服这些限制的技术。我们的实验结果表明，OXONE比基于关系的模式忽略方法快22倍，并且可扩展性更高。 OXONE和XyDiff（C版）的性能可比。但是，更重要的是，与较大的数据集相比，我们的方法与XyDiff相比具有更大的可伸缩性，并且其增量结果的质量比XyDiff更好。

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