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» CURE: An Efficient Clustering Algorithm for Large Databases
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139
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ICDE
2010
IEEE
491views Database» more  ICDE 2010»
16 years 3 months ago
TrajStore: An Adaptive Storage System for Very Large Trajectory Data Sets
The rise of GPS and broadband-speed wireless devices has led to tremendous excitement about a range of applications broadly characterized as "location based services". Cu...
Philippe Cudré-Mauroux, Eugene Wu, Samuel M...
141
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ICDT
2007
ACM
74views Database» more  ICDT 2007»
15 years 7 months ago
World-Set Decompositions: Expressiveness and Efficient Algorithms
Uncertain information is commonplace in real-world data management scenarios. The ability to represent large sets of possible instances (worlds) while supporting efficient storage ...
Lyublena Antova, Christoph Koch, Dan Olteanu
241
Voted
ICDE
2002
IEEE
209views Database» more  ICDE 2002»
16 years 5 months ago
Geometric-Similarity Retrieval in Large Image Bases
We propose a novel approach to shape-based image retrieval that builds upon a similarity criterion which is based on the average point set distance. Compared to traditional techni...
Ioannis Fudos, Leonidas Palios, Evaggelia Pitoura
143
Voted
BMCBI
2007
133views more  BMCBI 2007»
15 years 3 months ago
MATLIGN: a motif clustering, comparison and matching tool
Background: Sequence motifs representing transcription factor binding sites (TFBS) are commonly encoded as position frequency matrices (PFM) or degenerate consensus sequences (CS)...
Matti Kankainen, Ari Löytynoja
122
Voted
BIBE
2003
IEEE
116views Bioinformatics» more  BIBE 2003»
15 years 9 months ago
An Assessment of a Metric Space Database Index to Support Sequence Homology
Hierarchical metric-space clustering methods have been commonly used to organize proteomes into taxonomies. Consequently, it is often anticipated that hierarchical clustering can ...
Rui Mao, Weijia Xu, Neha Singh, Daniel P. Miranker