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» Minimization and Partitioning Method Reducing Input Sets
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KDD
2005
ACM
170views Data Mining» more  KDD 2005»
16 years 1 months ago
Parallel mining of closed sequential patterns
Discovery of sequential patterns is an essential data mining task with broad applications. Among several variations of sequential patterns, closed sequential pattern is the most u...
Shengnan Cong, Jiawei Han, David A. Padua
91
Voted
VLDB
1998
ACM
101views Database» more  VLDB 1998»
15 years 5 months ago
On Optimal Node Splitting for R-trees
The problem of finding an optimal bipartition of a rectangle set has a direct impact on query performance of dynamic R-trees. During update operations, overflowed nodes need to be...
Yván J. García, Mario A. Lopez, Scot...
NIPS
2001
15 years 2 months ago
Spectral Relaxation for K-means Clustering
The popular K-means clustering partitions a data set by minimizing a sum-of-squares cost function. A coordinate descend method is then used to nd local minima. In this paper we sh...
Hongyuan Zha, Xiaofeng He, Chris H. Q. Ding, Ming ...
105
Voted
CORR
2010
Springer
92views Education» more  CORR 2010»
15 years 1 months ago
Parameterizing by the Number of Numbers
The usefulness of parameterized algorithmics has often depended on what Niedermeier has called, "the art of problem parameterization." In this paper we introduce and expl...
Michael R. Fellows, Serge Gaspers, Frances A. Rosa...
ICPR
2000
IEEE
15 years 6 months ago
Statistical-Based Approach to Word Segmentation
Thispaper presents a text word extraction algorithm that takes a set of bounding boxes of glyphs and their associated text lines of a given document andpartitions the glyphs into ...
Yalin Wang, Robert M. Haralick, Ihsin T. Phillips