Effective Pruning for XML Structural Match Queries

Provided by: La Trobe University
Topic: Big Data
Format: PDF
Extensible Markup Language (XML) is becoming the de facto standard for exchanging information over the Internet, which results in the proliferation of XML documents. This paper has led to increased interest in this area by the research community. One of the main challenges is processing large collections of XML documents efficiently. Most current methods suffer from two drawbacks: an inability to complement each other to further enhance query processing performance without modifying the existing query processing engine; and an incapability of being customized for different structural and usage characteristics.

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