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SAC
2010
ACM
13 years 6 months ago
Optimal linear projections for enhancing desired data statistics
Problems involving high-dimensional data, such as pattern recognition, image analysis, and gene clustering, often require a preliminary step of dimension reduction before or durin...
Evgenia Rubinshtein, Anuj Srivastava
ICDAR
2009
IEEE
14 years 2 months ago
Robust Recognition of Documents by Fusing Results of Word Clusters
The word error rate of any optical character recognition system (OCR) is usually substantially below its component or character error rate. This is especially true of Indic langua...
Venkat Rasagna, Anand Kumar 0002, C. V. Jawahar, R...
CIKM
2000
Springer
14 years 7 days ago
Dimensionality Reduction and Similarity Computation by Inner Product Approximations
—As databases increasingly integrate different types of information such as multimedia, spatial, time-series, and scientific data, it becomes necessary to support efficient retri...
Ömer Egecioglu, Hakan Ferhatosmanoglu
SDM
2004
SIAM
162views Data Mining» more  SDM 2004»
13 years 9 months ago
Subspace Clustering of High Dimensional Data
Clustering suffers from the curse of dimensionality, and similarity functions that use all input features with equal relevance may not be effective. We introduce an algorithm that...
Carlotta Domeniconi, Dimitris Papadopoulos, Dimitr...
KDD
2000
ACM
149views Data Mining» more  KDD 2000»
13 years 11 months ago
Efficient clustering of high-dimensional data sets with application to reference matching
Many important problems involve clustering large datasets. Although naive implementations of clustering are computationally expensive, there are established efficient techniques f...
Andrew McCallum, Kamal Nigam, Lyle H. Ungar