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Journal of Computers EIMEDLINEScopus

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篇名 Orthogonal Range Search Approach Using FGBC-iDistance
卷期 31:5
作者 Xinpan Yuan 、 Qingyun Liu 、 Songlin Wang 、 Zhigao Zeng
頁次 044-060
關鍵字 FGBC-iDistance 、 high-dimensional 、 iDistance 、 orthogonal range 、 EI 、 MEDLINE 、 Scopus
出刊日期 202010
DOI 10.3966/199115992020103105004

中文摘要

英文摘要

Orthogonal range queries in high-dimensional data is extremely important and relevant. Not to modify the current index and use the inherent functionality of the existing indexing and retrieval mechanisms, there are three orthogonal range search approaches, including naïve, space and data-based approach. Naïve approach is to approximate orthogonal search by external query circle of iDistance. The space approach is mainly to break the orthogonal range search into multiple squares. A data-based approach by iDistance index is better than naïve and space. This paper proposed a more fine-grained partition on iDistance index, each part corresponded with a unique FGBC code (fine-grained bit code), which realizes the candidate sets filtered more precisely. The experimental results on the synthetic and real datasets proved that the FGBCiDistance is correct and effective.

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