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ECML
2006
Springer
14 years 2 months ago
Subspace Metric Ensembles for Semi-supervised Clustering of High Dimensional Data
A critical problem in clustering research is the definition of a proper metric to measure distances between points. Semi-supervised clustering uses the information provided by the ...
Bojun Yan, Carlotta Domeniconi
NIPS
1998
13 years 11 months ago
Restructuring Sparse High Dimensional Data for Effective Retrieval
The task in text retrieval is to find the subset of a collection of documents relevant to a user's information request, usually expressed as a set of words. Classically, docu...
Charles Lee Isbell Jr., Paul A. Viola
SIGMOD
2001
ACM
193views Database» more  SIGMOD 2001»
14 years 10 months ago
Epsilon Grid Order: An Algorithm for the Similarity Join on Massive High-Dimensional Data
The similarity join is an important database primitive which has been successfully applied to speed up applications such as similarity search, data analysis and data mining. The s...
Christian Böhm, Bernhard Braunmüller, Fl...
CIKM
2008
Springer
14 years 10 days ago
On low dimensional random projections and similarity search
Random projection (RP) is a common technique for dimensionality reduction under L2 norm for which many significant space embedding results have been demonstrated. However, many si...
Yu-En Lu, Pietro Liò, Steven Hand
COMSIS
2010
13 years 7 months ago
Effective semi-supervised nonlinear dimensionality reduction for wood defects recognition
Dimensionality reduction is an important preprocessing step in high-dimensional data analysis without losing intrinsic information. The problem of semi-supervised nonlinear dimensi...
Zhao Zhang, Ning Ye