Skip to search boxSkip to navigationSkip to main content

Bit-Vector Search Filtering with Application to a Kanji Dictionary

  • Matthew Skala
Research Output:
Conference Article in Proceeding or Book/Report chapter
Article in proceedings
Peer-review

Open access

Publication Information

Output type

Research Output:
Conference Article in Proceeding or Book/Report chapter
Article in proceedings
Peer-review

Original language

English

Pages from-to (Number of pages)

Pages 138-150

Publication milestones

  • Published - 2016

Publication status

Published - 2016

Publisher

Springer, United States, Germany

Book series

  • Book series name: Lecture Notes in Computer Science
    Volume: 9939
    ISSN: 0302-9743
978-3-319-46758-0

ISBN (Electronic)

978-3-319-46759-7

Publication IDs

  • Scopus: 84989831356

Host publication title

Similarity Search and Applications: 9th International Conference, SISAP 2016, Tokyo, Japan, October 24-26, 2016

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.

Publication metrics