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-reviewOpen access
Publication Information
Output type
Research Output:
Conference Article in Proceeding or Book/Report chapter
Article in proceedings
Peer-reviewOriginal language
EnglishPages from-to (Number of pages)
Pages 138-150Publication milestones
- Published - 2016
Publication status
Published - 2016
Publisher
Springer, United States, GermanyBook series
- Book series name: Lecture Notes in Computer Science
Volume: 9939
ISSN: 0302-9743
ISBN (Print)
978-3-319-46758-0ISBN (Electronic)
978-3-319-46759-7Publication IDs
- Scopus: 84989831356
Host publication title
Similarity Search and Applications: 9th International Conference, SISAP 2016, Tokyo, Japan, October 24-26, 2016Abstract
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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Accepted author manuscript, 1.02 MB
