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» Phenomenal Data Mining: From Data to Phenomena
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HUC
2011
Springer
14 years 6 months ago
iBAT: detecting anomalous taxi trajectories from GPS traces
GPS-equipped taxis can be viewed as pervasive sensors and the large-scale digital traces produced allow us to reveal many hidden “facts” about the city dynamics and human beha...
Daqing Zhang, Nan Li, Zhi-Hua Zhou, Chao Chen, Lin...
KDD
2008
ACM
161views Data Mining» more  KDD 2008»
16 years 7 months ago
Spectral domain-transfer learning
Traditional spectral classification has been proved to be effective in dealing with both labeled and unlabeled data when these data are from the same domain. In many real world ap...
Xiao Ling, Wenyuan Dai, Gui-Rong Xue, Qiang Yang, ...
KDD
2009
ACM
173views Data Mining» more  KDD 2009»
16 years 7 months ago
The offset tree for learning with partial labels
We present an algorithm, called the offset tree, for learning in situations where a loss associated with different decisions is not known, but was randomly probed. The algorithm i...
Alina Beygelzimer, John Langford
PAKDD
2005
ACM
103views Data Mining» more  PAKDD 2005»
16 years 8 days ago
Subgroup Discovery Techniques and Applications
This paper presents the advances in subgroup discovery and the ways to use subgroup discovery to generate actionable knowledge for decision support. Actionable knowledge is explici...
Nada Lavrac
188
Voted
AUSDM
2008
Springer
224views Data Mining» more  AUSDM 2008»
15 years 8 months ago
Customer Event Rate Estimation Using Particle Filters
Estimating the rate at which events happen has been studied under various guises and in different settings. We are interested in the specific case of consumerinitiated events or t...
Harsha Honnappa