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» Highly Scalable Rough Set Reducts Generation
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ICADL
2005
Springer
112views Education» more  ICADL 2005»
14 years 3 months ago
A Method for Creating a High Quality Collection of Researchers' Homepages from the Web
This paper proposes a method for creating a high quality collection of researchers’ homepages. The proposed method consists of three phases: rough filtering of the possible web p...
Yuxin Wang, Keizo Oyama
CCGRID
2010
IEEE
13 years 11 months ago
High Performance Dimension Reduction and Visualization for Large High-Dimensional Data Analysis
Abstract--Large high dimension datasets are of growing importance in many fields and it is important to be able to visualize them for understanding the results of data mining appro...
Jong Youl Choi, Seung-Hee Bae, Xiaohong Qiu, Geoff...
GRC
2005
IEEE
14 years 3 months ago
Discovering and ranking important rules
— Decision rules generated from reducts can fully describe a data set. We introduce a new method of evaluating rules by taking advantage of rough sets theory. We consider rules g...
Jiye Li, Nick Cercone
CIDM
2007
IEEE
14 years 4 months ago
Scalable Clustering for Large High-Dimensional Data Based on Data Summarization
Clustering large data sets with high dimensionality is a challenging data-mining task. This paper presents a framework to perform such a task efficiently. It is based on the notio...
Ying Lai, Ratko Orlandic, Wai Gen Yee, Sachin Kulk...
ICCAD
2006
IEEE
100views Hardware» more  ICCAD 2006»
14 years 6 months ago
Faster, parametric trajectory-based macromodels via localized linear reductions
— Trajectory-based methods offer an attractive methodology for automated, on-demand generation of macromodels for custom circuits. These models are generated by sampling the stat...
Saurabh K. Tiwary, Rob A. Rutenbar