DBSTC: an effective method for discovering cluster features with different spatiotemporal densities

DBSTC: an effective method for discovering cluster features with different spatiotemporal densities

Spatiotemporal clustering is one of the most advanced research topics in geospatial data mining. It has been challenging to discover cluster features with different spatiotemporal densities in geographic information data set. This paper presents an effective density-based spatiotemporal clustering a...

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Bibliographic Details
Main Authors: Zhenhong Du, Yuhua Gu, Chuanrong Zhang, Feng Zhang, Renyi Liu, Jean Sequeira
Format: Article
Language:English
Published: Taylor & Francis Group 2018-06-01
Series:International Journal of Digital Earth
Subjects:
data mining
spatiotemporal clustering
density-based clustering
ordered reachable time window distribution
shared nearest neighbor
Online Access:http://dx.doi.org/10.1080/17538947.2017.1338765

Internet

http://dx.doi.org/10.1080/17538947.2017.1338765

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