VXPath: A Visual XPath Query Evaluator
Weimin He, Teng Lv, Matthew Meis, Ping Yan
Abstract
Weimin He, Teng Lv, Matthew Meis, Ping Yan
Abstract
With the popularity of Extensible Markup Language (XML) as the new standard of data exchange on the web, a large number of data sources are represented or encoded in XML format. Therefore, querying and searching XML data on the web has attracted much attention in the database literature. In this research work, we developed a prototype software system named VXPath to facilitate the efficient evaluation of XPath queries over XML data. VXPath is a visual XPath query evaluator that allows the user to evaluate an XPath query by clicking the nodes in an expanding tree instead of typing the whole XPath query by hand. Our system supports most common XPath axes, such as child, descendant, predicate and so on. In order to handle XML documents in very large size, instead of loading the whole XML document into memory, we extracted a concise data synopsis termed structural summary from the original XML document to avoid the loading overhead for large XML document. We evaluated our system over the data from XMark and DBLP and our system can handle large XML documents up to gigabytes.
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With the popularity of Extensible Markup Language (XML) as the new standard of data exchange on the web, a large number of data sources are represented or encoded in XML format. Therefore, querying and searching XML data on the web has attracted much attention in the database literature. In this research work, we developed a prototype software system named VXPath to facilitate the efficient evaluation of XPath queries over XML data. VXPath is a visual XPath query evaluator that allows the user to evaluate an XPath query by clicking the nodes in an expanding tree instead of typing the whole XPath query by hand. Our system supports most common XPath axes, such as child, descendant, predicate and so on. In order to handle XML documents in very large size, instead of loading the whole XML document into memory, we extracted a concise data synopsis termed structural summary from the original XML document to avoid the loading overhead for large XML document. We evaluated our system over the data from XMark and DBLP and our system can handle large XML documents up to gigabytes.
Key concepts: XPath, Computer science, XML database, Streaming XML, XML validation, Information retrieval, XML Schema (W3C), XSLT