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EEE
2005
IEEE
14 years 2 months ago
Predicting the Survival or Failure of Click-and-Mortar Corporations
With the boom in e-business, several corporations have emerged in the late nineties that have primarily conducted their business through the Internet and the Web. They have come t...
Indranil Bose, Raktim Pal
ICDM
2003
IEEE
143views Data Mining» more  ICDM 2003»
14 years 2 months ago
Active Sampling for Feature Selection
In knowledge discovery applications, where new features are to be added, an acquisition policy can help select the features to be acquired based on their relevance and the cost of...
Sriharsha Veeramachaneni, Paolo Avesani
PKDD
2001
Springer
120views Data Mining» more  PKDD 2001»
14 years 1 months ago
Distinguishing Natural Language Processes on the Basis of fMRI-Measured Brain Activation
We present a method for distinguishing two subtly different mental states, on the basis of the underlying brain activation measured with fMRI. The method uses a classifier to lea...
Francisco Pereira, Marcel Just, Tom M. Mitchell
ICDM
2006
IEEE
193views Data Mining» more  ICDM 2006»
14 years 2 months ago
Feature Subset Selection on Multivariate Time Series with Extremely Large Spatial Features
Several spatio-temporal data collected in many applications, such as fMRI data in medical applications, can be represented as a Multivariate Time Series (MTS) matrix with m rows (...
Hyunjin Yoon, Cyrus Shahabi
KDD
1999
ACM
220views Data Mining» more  KDD 1999»
14 years 1 months ago
Efficient Mining of Emerging Patterns: Discovering Trends and Differences
We introduce a new kind of patterns, called emerging patterns (EPs), for knowledge discovery from databases. EPs are defined as itemsets whose supports increase significantly from...
Guozhu Dong, Jinyan Li