FAÇADE: A fast and effective approach to the discovery of dense clusters in noisy spatial data

Yu Qian; Gang Zhang; Kang Zhang

FAÇADE: A fast and effective approach to the discovery of dense clusters in noisy spatial data

Yu Qian^*, Gang Zhang, Kang Zhang

^*Corresponding author for this work

Research output: Contribution to journal › Conference article published in journal › peer-review

17 Citations (Scopus)

Abstract

FAÇADE (Fast and Automatic Clustering Approach to Data Engineering) is a spatial clustering tool that can discover clusters of different sizes, shapes, and densities in noisy spatial data. Compared with the existing clustering methods, FAÇADE has several advantages: first, it separates true data and noise more effectively. Second, most steps of FAÇADE are automatic. Third, it requires only O(nlogn) time. 2D and 3D visualizations are used in FAÇADE to assist parameter selection and result evaluation. More information on FAÇADE is available at: http://viscomp.utdallas.edu/ FACADE.

Original language	English
Pages (from-to)	921-922
Number of pages	2
Journal	Proceedings of the ACM SIGMOD International Conference on Management of Data
Publication status	Published - 2004
Externally published	Yes
Event	Proceedings of the ACM SIGMOD International Conference on Management of Data, SIGMOD 2004 - Paris, France Duration: 13 Jun 2004 → 18 Jun 2004

Cite this

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title = "FA{\c C}ADE: A fast and effective approach to the discovery of dense clusters in noisy spatial data",

abstract = "FA{\c C}ADE (Fast and Automatic Clustering Approach to Data Engineering) is a spatial clustering tool that can discover clusters of different sizes, shapes, and densities in noisy spatial data. Compared with the existing clustering methods, FA{\c C}ADE has several advantages: first, it separates true data and noise more effectively. Second, most steps of FA{\c C}ADE are automatic. Third, it requires only O(nlogn) time. 2D and 3D visualizations are used in FA{\c C}ADE to assist parameter selection and result evaluation. More information on FA{\c C}ADE is available at: http://viscomp.utdallas.edu/ FACADE.",

author = "Yu Qian and Gang Zhang and Kang Zhang",

year = "2004",

language = "English",

pages = "921--922",

journal = "Proceedings of the ACM SIGMOD International Conference on Management of Data",

issn = "0730-8078",

note = "Proceedings of the ACM SIGMOD International Conference on Management of Data, SIGMOD 2004 ; Conference date: 13-06-2004 Through 18-06-2004",

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T1 - FAÇADE

T2 - Proceedings of the ACM SIGMOD International Conference on Management of Data, SIGMOD 2004

AU - Qian, Yu

AU - Zhang, Gang

AU - Zhang, Kang

PY - 2004

Y1 - 2004

N2 - FAÇADE (Fast and Automatic Clustering Approach to Data Engineering) is a spatial clustering tool that can discover clusters of different sizes, shapes, and densities in noisy spatial data. Compared with the existing clustering methods, FAÇADE has several advantages: first, it separates true data and noise more effectively. Second, most steps of FAÇADE are automatic. Third, it requires only O(nlogn) time. 2D and 3D visualizations are used in FAÇADE to assist parameter selection and result evaluation. More information on FAÇADE is available at: http://viscomp.utdallas.edu/ FACADE.

AB - FAÇADE (Fast and Automatic Clustering Approach to Data Engineering) is a spatial clustering tool that can discover clusters of different sizes, shapes, and densities in noisy spatial data. Compared with the existing clustering methods, FAÇADE has several advantages: first, it separates true data and noise more effectively. Second, most steps of FAÇADE are automatic. Third, it requires only O(nlogn) time. 2D and 3D visualizations are used in FAÇADE to assist parameter selection and result evaluation. More information on FAÇADE is available at: http://viscomp.utdallas.edu/ FACADE.

UR - http://www.scopus.com/inward/record.url?scp=3142740971&partnerID=8YFLogxK

M3 - Conference article published in journal

AN - SCOPUS:3142740971

SN - 0730-8078

SP - 921

EP - 922

JO - Proceedings of the ACM SIGMOD International Conference on Management of Data

JF - Proceedings of the ACM SIGMOD International Conference on Management of Data

Y2 - 13 June 2004 through 18 June 2004

ER -

FAÇADE: A fast and effective approach to the discovery of dense clusters in noisy spatial data

Abstract

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