From Partition-Based Clustering to Density-Based Clustering: Fast Find Clusters With Diverse Shapes and Densities in Spatial Databases

From Partition-Based Clustering to Density-Based Clustering: Fast Find Clusters With Diverse Shapes and Densities in Spatial Databases

Spatial data clustering has played an important role in the knowledge discovery in spatial databases. However, due to the increasing volume and diversity of data, conventional spatial clustering methods are inefficient even on moderately large data sets, and usually fail to discover clusters with di...

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Bibliographic Details
Main Authors: Jiang Wang, Cheng Zhu, Yun Zhou, Xianqiang Zhu, Yilin Wang, Weiming Zhang
Format: Article
Language:English
Published: IEEE 2018-01-01
Series:IEEE Access
Subjects:
Spatial clustering
partition-and-merge strategy
diverse shapes and densities
efficiency on large spatial databases
Online Access:https://ieeexplore.ieee.org/document/8166726/

Internet

https://ieeexplore.ieee.org/document/8166726/

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