Please use this identifier to cite or link to this item: https://scholarbank.nus.edu.sg/handle/10635/40736
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dc.titleXR-Tree: Indexing XML data for efficient structural joins
dc.contributor.authorJiang, H.
dc.contributor.authorLu, H.
dc.contributor.authorWang, W.
dc.contributor.authorOoi, B.C.
dc.date.accessioned2013-07-04T08:11:10Z
dc.date.available2013-07-04T08:11:10Z
dc.date.issued2003
dc.identifier.citationJiang, H.,Lu, H.,Wang, W.,Ooi, B.C. (2003). XR-Tree: Indexing XML data for efficient structural joins. Proceedings - International Conference on Data Engineering : 253-264. ScholarBank@NUS Repository.
dc.identifier.urihttp://scholarbank.nus.edu.sg/handle/10635/40736
dc.description.abstractXML documents are typically queried with a combination of value search and structure search. While querying by values can leverage traditional database technologies, evaluating structural relationship, specifically parent-child or ancestor-descendant relationship, between XML element sets has imposed a great challenge on efficient XML query processing. This paper proposes XR-tree, namely, XML Region Tree, which is a dynamic external memory index structure specially designed for strictly nested XML data. The unique feature of XR-tree is that, for a given element, all its ancestors (or descendants) in an element set indexed by an XR-tree can be identified with optimal worst case I/O cost. We then propose a new structural join algorithm that can evaluate the structural relationship between two XR-tree indexed element sets by effectively skipping ancestors and descendants that do not participate in the join. Our extensive performance study shows that the XR-tree based join algorithm significantly outperforms previous algorithms.
dc.sourceScopus
dc.typeConference Paper
dc.contributor.departmentCOMPUTER SCIENCE
dc.description.sourcetitleProceedings - International Conference on Data Engineering
dc.description.page253-264
dc.description.codenPIDEE
dc.identifier.isiutNOT_IN_WOS
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