Develop spatial learning indexing using improved K-means clustering partition(基于改进的K-means聚类分区均匀化空间学习索引)

Develop spatial learning indexing using improved K-means clustering partition(基于改进的K-means聚类分区均匀化空间学习索引)

With the rapid increase of data size, the defects of traditional spatial indexing become more and more apparent. In comparison, learning indexing is based on data distribution. Its volume will not expand with the increase of the amount of data, and can achieve better performance without performing h...

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Bibliographic Details
Main Authors: 傅晨华(FU Chenhua), 张丰(ZHANG Feng), 胡林舒(HU Linshu), 王立君(WANG Lijun)
Format: Article
Language:zho
Published: Zhejiang University Press 2024-03-01
Series:Zhejiang Daxue xuebao. Lixue ban
Subjects:
learned index(学习索引)
k-means clustering(k-means聚类)
space filling curve(空间填充曲线)
spatial index(空间索引)
Online Access:https://doi.org/10.3785/j.issn.1008-9497.2024.02.003

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