Scalable Hybrid Search on Distributed Databases

  • Jungkee Kim
  • Geoffrey Fox
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3516)


We have previously described a hybrid keyword search that combines metadata search with a traditional keyword search over unstructured context data. This hybrid search paradigm provides the inquirer additional options to narrow the search with some semantic aspect from the XML metadata query. But in earlier work, we experienced the scalability limitations of a single-machine implementation. In this paper, we describe a scalable hybrid search on distributed databases. This scalable hybrid search provides a total query result from the collection of individual inquiries against independent data fragments distributed in a computer cluster. We demonstrate our architecture extends the scalability of a native XML query limited in a single machine and improves the performance for some queries.


Query Processing Query Result Query Time Average Response Time Query Message 
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 2005

Authors and Affiliations

  • Jungkee Kim
    • 1
    • 2
  • Geoffrey Fox
    • 2
  1. 1.Department of Computer ScienceFlorida State UniversityTallahasseeU.S.A
  2. 2.Community Grids LaboratoryIndiana UniversityBloomingtonU.S.A

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