Research on the Parallelization of the DBSCAN Clustering Algorithm for Spatial Data Mining Based on the Spark Platform

Research on the Parallelization of the DBSCAN Clustering Algorithm for Spatial Data Mining Based on the Spark Platform

Density-based spatial clustering of applications with noise (DBSCAN) is a density-based clustering algorithm that has the characteristics of being able to discover clusters of any shape, effectively distinguishing noise points and naturally supporting spatial databases. DBSCAN has been widely used i...

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Bibliographic Details
Main Authors: Fang Huang, Qiang Zhu, Ji Zhou, Jian Tao, Xiaocheng Zhou, Du Jin, Xicheng Tan, Lizhe Wang
Format: Article
Language:English
Published: MDPI AG 2017-12-01
Series:Remote Sensing
Subjects:
spatial data mining
DBSCAN algorithm
parallel computing
spark platform
traffic congestion area discovery
Online Access:https://www.mdpi.com/2072-4292/9/12/1301

Internet

https://www.mdpi.com/2072-4292/9/12/1301

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