Combinatorial optimization: algorithms and complexity
Combinatorial optimization: algorithms and complexity
Relational Databases for Querying XML Documents: Limitations and Opportunities
VLDB '99 Proceedings of the 25th International Conference on Very Large Data Bases
What makes the differences: benchmarking XML database implementations
ACM Transactions on Internet Technology (TOIT)
Detecting changes on unordered XML documents using relational databases: a schema-conscious approach
Proceedings of the 14th ACM international conference on Information and knowledge management
XANDY: a scalable change detection technique for ordered XML documents using relational databases
Data & Knowledge Engineering - Special issue: WIDM 2004
XANDY: detecting changes on large unordered XML documents using relationalDatabases
DASFAA'05 Proceedings of the 10th international conference on Database Systems for Advanced Applications
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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.