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SDM
2009
SIAM
205views Data Mining» more  SDM 2009»
14 years 5 months ago
Identifying Information-Rich Subspace Trends in High-Dimensional Data.
Identifying information-rich subsets in high-dimensional spaces and representing them as order revealing patterns (or trends) is an important and challenging research problem in m...
Chandan K. Reddy, Snehal Pokharkar
ICDE
2009
IEEE
290views Database» more  ICDE 2009»
14 years 9 months ago
GraphSig: A Scalable Approach to Mining Significant Subgraphs in Large Graph Databases
Graphs are being increasingly used to model a wide range of scientific data. Such widespread usage of graphs has generated considerable interest in mining patterns from graph datab...
Sayan Ranu, Ambuj K. Singh
IRI
2003
IEEE
14 years 1 months ago
Damage Pattern Mining in Hurricane Image Databases
– We present a damage pattern mining framework for hurricane data on residential houses using aerial photographs with 1:3000 based scale. The vertical photographs are normally co...
Shu-Ching Chen, Mei-Ling Shyu, Chengcui Zhang, Wal...
EWCBR
2006
Springer
13 years 11 months ago
Rough Set Feature Selection Algorithms for Textual Case-Based Classification
Feature selection algorithms can reduce the high dimensionality of textual cases and increase case-based task performance. However, conventional algorithms (e.g., information gain)...
Kalyan Moy Gupta, David W. Aha, Philip Moore
ICANN
2009
Springer
13 years 11 months ago
Profiling of Mass Spectrometry Data for Ovarian Cancer Detection Using Negative Correlation Learning
This paper proposes a novel Mass Spectrometry data profiling method for ovarian cancer detection based on negative correlation learning (NCL). A modified Smoothed Nonlinear Energy ...
Shan He, Huanhuan Chen, Xiaoli Li, Xin Yao