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        <identifier>oai:drops-oai.dagstuhl.de:229</identifier>
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          <dc:title>Node Identification Schemes for Efficient XML Retrieval</dc:title>
          <dc:creator>Weigel, Felix</dc:creator>
          <dc:creator>Schulz, Klaus U.</dc:creator>
          <dc:creator>Meuss, Holger</dc:creator>
          <dc:subject>node identification scheme</dc:subject>
          <dc:subject>labelling scheme</dc:subject>
          <dc:subject>numbering scheme</dc:subject>
          <dc:subject>naming scheme</dc:subject>
          <dc:subject>tree encoding</dc:subject>
          <dc:subject>BIRD</dc:subject>
          <dc:description>Node identifiers (IDs) encoding part of the tree structure in XML documents can save I/O for table look-ups,&#13;
thus speeding up the evaluation of path and tree queries on large persistent document collections. In&#13;
particular, binary tree relations such as the extended XPath axes can be either decided for a given pair of&#13;
node IDs, or reconstructed for a single node ID, without access to secondary storage. Several ID schemes have&#13;
been proposed so far, which differ with respect to (1) expressiveness, i.e. which relations can be&#13;
decided or reconstructed from IDs, (2) the runtime performance and asymptotic behaviour of decision and&#13;
reconstruction operations, (3) the storage overhead for the IDs, and (4) robustness, i.e. behaviour in the&#13;
presence of updates. First we review five ID schemes, positioning them in the trade-off between these four comparison&#13;
criteria. Then a new ID scheme called BIRD, for Balanced Index-based ID scheme for Reconstruction and&#13;
Decision, is introduced and illustrated throughout several examples of decision and reconstruction operations&#13;
on IDs. We argue that emphasizing runtime performance and expressive power, BIRDs strategy in the above&#13;
trade-off is best for many applications, especially where storage minimization is not the primary goal and&#13;
updates occur in a bulk-fashion rather than in realtime. Our experimental results on document collections of&#13;
up to one gigabyte prove BIRD to be most efficient in terms of expressiveness and runtime performance. Most&#13;
notably, BIRD is the only scheme to support both decision and reconstruction of many relations in constant&#13;
time. But also in terms of storage and robustness BIRD is highly competitive.</dc:description>
          <dc:publisher>Schloss Dagstuhl – Leibniz-Zentrum für Informatik</dc:publisher>
          <dc:contributor>Felix Weigel and Klaus U. Schulz and Holger Meuss</dc:contributor>
          <dc:date>2005</dc:date>
          <dc:relation>Is Part Of Dagstuhl Seminar Proceedings, Volume 5061, Foundations of Semistructured Data (2005)</dc:relation>
          <dc:type>InProceedings</dc:type>
          <dc:type>Text</dc:type>
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          <dc:identifier>doi:10.4230/DagSemProc.05061.6</dc:identifier>
          <dc:identifier>urn:nbn:de:0030-drops-2292</dc:identifier>
          <dc:identifier>https://drops.dagstuhl.de/entities/document/10.4230/DagSemProc.05061.6</dc:identifier>
          <dc:language>eng</dc:language>
          <dc:rights>https://creativecommons.org/licenses/by/4.0/legalcode</dc:rights>
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