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» CURE: An Efficient Clustering Algorithm for Large Databases
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BMCBI
2010
172views more  BMCBI 2010»
15 years 4 months ago
Accessing the SEED genome databases via Web services API: tools for programmers
Background: The SEED integrates many publicly available genome sequences into a single resource. The database contains accurate and up-to-date annotations based on the subsystems ...
Terry Disz, Sajia Akhter, Daniel Cuevas, Robert Ol...
OSDI
2008
ACM
16 years 4 months ago
Hunting for Problems with Artemis
Artemis is a modular application designed for analyzing and troubleshooting the performance of large clusters running datacenter services. Artemis is composed of four modules: (1)...
Gabriela F. Cretu-Ciocarlie, Mihai Budiu, Mois&eac...
JCP
2008
171views more  JCP 2008»
15 years 4 months ago
Mining Frequent Subgraph by Incidence Matrix Normalization
Existing frequent subgraph mining algorithms can operate efficiently on graphs that are sparse, have vertices with low and bounded degrees, and contain welllabeled vertices and edg...
Jia Wu, Ling Chen
WWW
2002
ACM
16 years 4 months ago
Translating XSLT programs to Efficient SQL queries
We present an algorithm for translating XSLT programs into SQL. Our context is that of virtual XML publishing, in which a single XML view is defined from a relational database, an...
Sushant Jain, Ratul Mahajan, Dan Suciu
IJCV
2008
157views more  IJCV 2008»
15 years 3 months ago
Pairwise Matching of 3D Fragments Using Cluster Trees
Abstract We propose a novel and efficient surface matching approach for reassembling broken solids as well as for matching assembly components using cluster trees of oriented point...
Simon Winkelbach, Friedrich M. Wahl