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. In this paper, we propose a highperformance XML pro cessing method using a novel pattern recognition algorithm based on a grammar compression algorithm. In the method, training XML documents are preanalyzed in order to de tect frequently appearing constructs in the document. The extended XML parser uses the results of the preanalysis to make its parsing faster with speculative input matching. The results of experiments show that the proposed method improves the performance of XML parsing by up to 182% (146% on average) compared with an ordinary SAX parser with namespace processing under the condition that the tar get XML documents are similar to the preanalyzed XML
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Recognizing Matching Patterns for XML Data Using Grammarbased Data Compression Algorithm