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Effectively Inferring the Search-for Node Type in XML Keyword Search

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Database Systems for Advanced Applications (DASFAA 2010)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 5981))

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Abstract

xml keyword search provides a simple and user-friendly way of retrieving data from xml databases, but the ambiguities of keywords make it difficult to effectively answer keyword queries. XReal [4] utilizes the statistics of underlying data to resolve keyword ambiguity problems. However, we found their proposed formula for inferring the search-for node type suffers from inconsistency and abnormality problems.

In this paper, we propose a dynamic reduction factor scheme as well as a novel algorithm DynamicInfer to resolve these two problems. Experimental results are provided to verify the effectiveness of our approach.

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References

  1. http://www.cs.washington.edu/research/xmldatasets

  2. http://www.oracle.com/database/berkeley-db/

  3. http://xmlsoft.org/

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Li, J., Wang, J. (2010). Effectively Inferring the Search-for Node Type in XML Keyword Search. In: Kitagawa, H., Ishikawa, Y., Li, Q., Watanabe, C. (eds) Database Systems for Advanced Applications. DASFAA 2010. Lecture Notes in Computer Science, vol 5981. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-12026-8_11

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  • DOI: https://doi.org/10.1007/978-3-642-12026-8_11

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-12025-1

  • Online ISBN: 978-3-642-12026-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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