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KDD
2009
ACM
198views Data Mining» more  KDD 2009»
16 years 4 months ago
Pervasive parallelism in data mining: dataflow solution to co-clustering large and sparse Netflix data
All Netflix Prize algorithms proposed so far are prohibitively costly for large-scale production systems. In this paper, we describe an efficient dataflow implementation of a coll...
Srivatsava Daruru, Nena M. Marin, Matt Walker, Joy...
134
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KDD
2008
ACM
181views Data Mining» more  KDD 2008»
16 years 4 months ago
Learning subspace kernels for classification
Kernel methods have been applied successfully in many data mining tasks. Subspace kernel learning was recently proposed to discover an effective low-dimensional subspace of a kern...
Jianhui Chen, Shuiwang Ji, Betul Ceran, Qi Li, Min...
133
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KDD
2007
ACM
141views Data Mining» more  KDD 2007»
16 years 4 months ago
Mining favorable facets
The importance of dominance and skyline analysis has been well recognized in multi-criteria decision making applications. Most previous studies assume a fixed order on the attribu...
Raymond Chi-Wing Wong, Jian Pei, Ada Wai-Chee Fu, ...
153
Voted
KDD
2007
ACM
165views Data Mining» more  KDD 2007»
16 years 4 months ago
Efficient and effective explanation of change in hierarchical summaries
Dimension attributes in data warehouses are typically hierarchical (e.g., geographic locations in sales data, URLs in Web traffic logs). OLAP tools are used to summarize the measu...
Deepak Agarwal, Dhiman Barman, Dimitrios Gunopulos...
161
Voted
KDD
2006
ACM
180views Data Mining» more  KDD 2006»
16 years 4 months ago
Learning the unified kernel machines for classification
Kernel machines have been shown as the state-of-the-art learning techniques for classification. In this paper, we propose a novel general framework of learning the Unified Kernel ...
Steven C. H. Hoi, Michael R. Lyu, Edward Y. Chang