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» Improving data mining utility with projective sampling
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98
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KDD
2005
ACM
118views Data Mining» more  KDD 2005»
15 years 10 months ago
On the use of linear programming for unsupervised text classification
We propose a new algorithm for dimensionality reduction and unsupervised text classification. We use mixture models as underlying process of generating corpus and utilize a novel,...
Mark Sandler
CIKM
2001
Springer
15 years 1 months ago
Sliding-Window Filtering: An Efficient Algorithm for Incremental Mining
We explore in this paper an effective sliding-window filtering (abbreviatedly as SWF) algorithm for incremental mining of association rules. In essence, by partitioning a transact...
Chang-Hung Lee, Cheng-Ru Lin, Ming-Syan Chen
ACML
2009
Springer
15 years 4 months ago
Injecting Structured Data to Generative Topic Model in Enterprise Settings
Enterprises have accumulated both structured and unstructured data steadily as computing resources improve. However, previous research on enterprise data mining often treats these ...
Han Xiao, Xiaojie Wang, Chao Du
SDM
2009
SIAM
152views Data Mining» more  SDM 2009»
15 years 6 months ago
Multiple Kernel Clustering.
Maximum margin clustering (MMC) has recently attracted considerable interests in both the data mining and machine learning communities. It first projects data samples to a kernel...
Bin Zhao, James T. Kwok, Changshui Zhang
73
Voted
ICDM
2009
IEEE
120views Data Mining» more  ICDM 2009»
15 years 4 months ago
Least Square Incremental Linear Discriminant Analysis
Abstract—Linear discriminant analysis (LDA) is a wellknown dimension reduction approach, which projects highdimensional data into a low-dimensional space with the best separation...
Li-Ping Liu, Yuan Jiang, Zhi-Hua Zhou