Abstract
As eXtensible Markup Language (XML) has become an emerging standard for information exchange on the World Wide Web, it has gained attention in database communities to extract information from XML seen as a database model. Data in XML can be mapped to a semistructured data model based on edge-labeled graph, and queries can be processed against it. Here, we propose new query optimization techniques using document type definitions which have the schema information about XML data. Our techniques reduce the large search space significantly while at the same time requiring less memory compared to the traditional index techniques. Also, as they preserve source database’s structure, they can process many kinds of complex queries. We implemented our techniques and provided preliminary performance results.
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