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» Practical Preference Relations for Large Data Sets
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APVIS
2010
13 years 10 months ago
GMap: Visualizing graphs and clusters as maps
Information visualization is essential in making sense out of large data sets. Often, high-dimensional data are visualized as a collection of points in 2-dimensional space through...
Emden R. Gansner, Yifan Hu, Stephen G. Kobourov
BMCBI
2010
121views more  BMCBI 2010»
13 years 5 months ago
A grammar-based distance metric enables fast and accurate clustering of large sets of 16S sequences
Background: We propose a sequence clustering algorithm and compare the partition quality and execution time of the proposed algorithm with those of a popular existing algorithm. T...
David J. Russell, Samuel F. Way, Andrew K. Benson,...
IDA
2005
Springer
14 years 1 months ago
Learning Label Preferences: Ranking Error Versus Position Error
We consider the problem of learning a ranking function, that is a mapping from instances to rankings over a finite number of labels. Our learning method, referred to as ranking by...
Eyke Hüllermeier, Johannes Fürnkranz
IEEECIT
2006
IEEE
14 years 2 months ago
A Complexity Metrics Set for Large-Scale Object-Oriented Software Systems
Although traditional software metrics have widely been applied to practical software projects, they have insufficient abilities to measure a large-scale system’s complexity at h...
Yutao Ma, Keqing He, Dehui Du, Jing Liu, Yulan Yan
SDM
2004
SIAM
211views Data Mining» more  SDM 2004»
13 years 9 months ago
Using Support Vector Machines for Classifying Large Sets of Multi-Represented Objects
Databases are a key technology for molecular biology which is a very data intensive discipline. Since molecular biological databases are rather heterogeneous, unification and data...
Hans-Peter Kriegel, Peer Kröger, Alexey Pryak...