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XML is a standard format for data exchange and it is well suited to represent internet applications because of its text-based format. However, this flexibility means that it incurs higher data processing overhead than ordinary data formats. This paper proposes a high-performance XML processing method using a novel pattern recognition algorithm based on a grammar compression algorithm. In the method, training XML documents are pre-analyzed in order to detect frequently appearing constructs in the document. The extended XML parser uses the results of the pre-analysis to make its parsing faster with speculative input matching.
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