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» Practical Preference Relations for Large Data Sets
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APVIS
2010
14 years 11 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»
14 years 7 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
15 years 3 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
15 years 3 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»
14 years 11 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...