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Location Based Services (LBS) have become extremely popular and used by millions of users.
Linear clustering of objects with multiple attributes
H. V. Jagadish · 1990
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A density-based algorithm for discovering clusters in large spatial databases with noise
M. Ester, H.-P. Kriegel, J. Sander, and X. Xu · 1996
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An efficient approach to clustering in large multimedia databases with noise
A. Hinneburg and D. A. Keim · 1998
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Chameleon: Hierarchical clustering using dynamic modeling
G. Karypis, E.-H. Han, and V. Kumar · 1999
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On clustering validation techniques
M. Halkidi, Y. Batistakis, and M. Vazirgiannis · 2001
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Analysis of the clustering properties of the hilbert space-filling curve
B. Moon, H. V. Jagadish, C. Faloutsos, and J. H. Saltz · 2001
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Analysis of multi-dimensional space-filling curves
M. F. Mokbel, W. G. Aref, and I. Kamel · 2003
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A survey of clustering data mining techniques
P. Berkhin · 2006
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Border: efficient computation of boundary points
C. Xia, W. Hsu, M. L. Lee, and B. C. Ooi · 2006
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Brim: An efficient boundary points detecting algorithm
B.-Z. Qiu, F. Yue, and J.-Y. Shen · 2007
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Sampling hidden objects using nearest-neighbor oracles
N. Dalvi, R. Kumar, A. Machanavajjhala, and V. Rastogi · 2011
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http://www.census.gov/2010census/data/
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Dissecting foursquare venue popularity via random region sampling
Y. Li, M. Steiner, L. Wang, Z.-L. Zhang, and J. Bao · 2012
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An efficient sampling method for characterizing points of interests on maps
P. Wang and et.al · 2014
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Optimality of clustering properties of space-filling curves
P. Xu and S. Tirthapura · 2014
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Aggregate estimations over location based services
W. Liu, M. F. Rahman, S. Thirumuruganathan, N. Zhang, and G. Das · 2015
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Crawling hidden objects with kNN queries
H. Yan, Z. Gong, N. Zhang, T. Huang, H. Zhong, and J. Wei · 2016
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