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Titlebook: Database and XML Technologies; Third International Stéphane Bressan,Stefano Ceri,Rainer Unland Conference proceedings 2005 Springer-Verlag

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楼主: legerdemain
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Approximate Subtree Identification in Heterogeneous XML Documents Collectionstern and subtrees of documents in the collection. An efficient algorithm for the identification of document subtrees, approximately conforming to the pattern, by indexing structures is then introduced.
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Optimizing Runtime XML Processing in Relational Databasesspects of XML processing in relational database systems using Microsoft. SQL Server. 2005’s approach as an example. It also motivates a non-textual storage as the preferred choice for storing XML natively. A performance evaluation of these techniques shows XML query performance improvements of up to 6 times.
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https://doi.org/10.1007/978-3-642-54681-5 insufficient to allow testing for various performance aspects, thus, the users of the repository must be able to add new data sets and/or queries for specific performance assessment tasks. We present our methodology for constructing the micro-benchmark repository, and illustrate with some sample micro-benchmarks.
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The Role of Groundwater During Drought. Specifically, we present solutions to four integration tasks: definition of complex mappings from relational sources to XML, distributed XQuery processing, generation of heterogeneous output formats, and the integration of heterogeneous data visualization and analysis tools.
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Theories of Coping with Chronic Stressent techniques that leverage the power of existing, state of the art methods, to efficiently support positional predicates as well. Our preliminary experimental comparisons with alternative approaches reveal the performance benefits of the proposed techniques.
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Thomas Bausch,Madeleine Koch,Alexander Vesertern and subtrees of documents in the collection. An efficient algorithm for the identification of document subtrees, approximately conforming to the pattern, by indexing structures is then introduced.
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A Framework for XML-Based Integration of Data, Visualization and Analysis in a Biomedical Domain. Specifically, we present solutions to four integration tasks: definition of complex mappings from relational sources to XML, distributed XQuery processing, generation of heterogeneous output formats, and the integration of heterogeneous data visualization and analysis tools.
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