An algorithm for clustering spatial lines based on connectivity for GML data

Author

Liu, Sheng ; Ji, Genlin ; Li, Wenjun

Author_Institution

Key Lab. of Virtual Geographic Environ., Nanjing Normal Univ., Nanjing, China

fYear

2011

fDate

June 29 2011-July 1 2011

Firstpage

44

Lastpage

47

Abstract

Algorithm SLC is proposed for clustering spatial lines based on connectivity for GML data. At beginning the intersection relations of spatial lines between each other are computed, and then the connectivity of spatial lines is computed by intersection relations, finally spatial lines are clustered by algorithm K-means with a novel similarity measurement method based on the connectivity. The experimental results show the algorithm SLC is effective and efficient.

Keywords

geographic information systems; hypermedia markup languages; pattern clustering; GML data connectivity; K-means algorithm; SLC abstract; geography mark-up language; intersection relations; spatial line clustering; Algorithm design and analysis; Classification algorithms; Clustering algorithms; Computer science; Data mining; Object recognition; Spatial databases; intersection relation; spatial clustering; spatial lines clustering; spatial lines connectivity; spatial topology;

fLanguage

English

Publisher

ieee

Conference_Titel

Spatial Data Mining and Geographical Knowledge Services (ICSDM), 2011 IEEE International Conference on

Conference_Location

Fuzhou

Print_ISBN

978-1-4244-8352-5

Type

conf

DOI

10.1109/ICSDM.2011.5969002

Filename

5969002