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» Applying Grid Technologies to Distributed Data Mining
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KDD
2008
ACM
137views Data Mining» more  KDD 2008»
14 years 8 months ago
Learning classifiers from only positive and unlabeled data
The input to an algorithm that learns a binary classifier normally consists of two sets of examples, where one set consists of positive examples of the concept to be learned, and ...
Charles Elkan, Keith Noto
WWW
2010
ACM
14 years 3 months ago
Collaborative location and activity recommendations with GPS history data
With the increasing popularity of location-based services, such as tour guide and location-based social network, we now have accumulated many location data on the Web. In this pap...
Vincent Wenchen Zheng, Yu Zheng, Xing Xie, Qiang Y...
IQIS
2005
ACM
14 years 1 months ago
Exploiting relationships for object consolidation
Researchers in the data mining area frequently have to spend significant portion of their time on preprocessing the data in order to apply their algorithms to real-world datasets...
Zhaoqi Chen, Dmitri V. Kalashnikov, Sharad Mehrotr...
ICDCS
2010
IEEE
13 years 12 months ago
Sentomist: Unveiling Transient Sensor Network Bugs via Symptom Mining
—Wireless Sensor Network (WSN) applications are typically event-driven. While the source codes of these applications may look simple, they are executed with a complicated concurr...
Yangfan Zhou, Xinyu Chen, Michael R. Lyu, Jiangchu...
FGCS
2006
111views more  FGCS 2006»
13 years 8 months ago
Collaborative data visualization for Earth Sciences with the OptIPuter
Collaborative visualization of large-scale datasets across geographically distributed sites is becoming increasingly important for Earth Sciences. Not only does it enhance our und...
Nut Taesombut, Xinran (Ryan) Wu, Andrew A. Chien, ...