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International Conference on Similarity Search and Applications

SISAP 2016: Similarity Search and Applications pp 137–150Cite as

Bit-Vector Search Filtering with Application to a Kanji Dictionary

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Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 9939))

Abstract

Database query problems can be categorized by the expressiveness of their query languages, and data structure bounds are better for less expressive languages. Highly expressive languages, such as those permitting Boolean operations, lead to difficult query problems with poor bounds, and high dimensionality in geometric problems also causes their query languages to become expressive and inefficient. The IDSgrep kanji dictionary software approaches a highly expressive tree-matching query problem with a filtering technique set in 128-bit Hamming space. It can be a model for other highly expressive query languages. We suggest improvements to bit vector filtering of general applicability, and evaluate them in the context of IDSgrep.

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Author information

Authors and Affiliations

  1. IT University of Copenhagen, Copenhagen, Denmark

    Matthew Skala

Authors
  1. Matthew Skala
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Correspondence to Matthew Skala .

Editor information

Editors and Affiliations

  1. CNRS–IRISA , Rennes, France

    Laurent Amsaleg

  2. National Institute of Informatics , Tokyo, Japan

    Michael E. Houle

  3. Ludwig-Maximilians-Universität München , München, Germany

    Erich Schubert

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Skala, M. (2016). Bit-Vector Search Filtering with Application to a Kanji Dictionary. In: Amsaleg, L., Houle, M., Schubert, E. (eds) Similarity Search and Applications. SISAP 2016. Lecture Notes in Computer Science(), vol 9939. Springer, Cham. https://doi.org/10.1007/978-3-319-46759-7_11

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  • DOI: https://doi.org/10.1007/978-3-319-46759-7_11

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-46758-0

  • Online ISBN: 978-3-319-46759-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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