SINBAD: Towards Structure-Independent Querying of Common Neighbors in XML Databases

  • Ba Quan Truong
  • Sourav S. Bhowmick
  • Curtis Dyreson
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7238)


xml query languages use directional path expressions to locate data in an xml data collection. They are tightly coupled to the structure of a data collection, and can fail when evaluated on the same data in a different structure. This paper extends XPath expressions with a new structure-independent, non-directional axis called the neighborhood axis. Given a pair of context nodes, the neighborhood axis returns those nodes that are common neighbors of the context nodes in any direction. Such axis finds its usefulness in structure-independent query formulation as well as supporting relevant results computation in design-independent xml keyword search. We propose an algorithm called sinbad that exploits the novel notion of node locality and small size of xml structure tree to efficiently determine the common neighbors of the context nodes. Our empirical study demonstrates that sinbad, built on top of an existing path materialization-based relational storage scheme, has promising query performance.


Child Node Node Locality Common Neighbor Full Document Manager Node 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Ba Quan Truong
    • 1
  • Sourav S. Bhowmick
    • 1
  • Curtis Dyreson
    • 2
  1. 1.School of Computer EngineeringNanyang Technological UniversitySingapore
  2. 2.Department of Computer ScienceUtah State UniversityUSA

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