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SIGMOD
2009
ACM
171views Database» more  SIGMOD 2009»
14 years 7 months ago
GAMPS: compressing multi sensor data by grouping and amplitude scaling
We consider the problem of collectively approximating a set of sensor signals using the least amount of space so that any individual signal can be efficiently reconstructed within...
Sorabh Gandhi, Suman Nath, Subhash Suri, Jie Liu
KDD
2008
ACM
232views Data Mining» more  KDD 2008»
14 years 8 months ago
Anticipating annotations and emerging trends in biomedical literature
The BioJournalMonitor is a decision support system for the analysis of trends and topics in the biomedical literature. Its main goal is to identify potential diagnostic and therap...
Bernd Wachmann, Dmitriy Fradkin, Fabian Mörch...
CGA
1999
13 years 7 months ago
Visualizing Large Telecommunication Data Sets
displays to abstract network data and let users interactwithit.Wehaveimplementedafull-scaleSwift3D prototype, which generated the examples we present here. Swift-3D We developed Sw...
Eleftherios Koutsofios, Stephen C. North, Daniel A...
KAIS
2008
221views more  KAIS 2008»
13 years 7 months ago
Forecasting skewed biased stochastic ozone days: analyses, solutions and beyond
Much work on skewed, stochastic, high dimensional, and biased datasets usually implicitly solve each problem separately. Recently, we have been approached by Texas Commission on En...
Kun Zhang, Wei Fan
KDD
2008
ACM
259views Data Mining» more  KDD 2008»
14 years 8 months ago
Using ghost edges for classification in sparsely labeled networks
We address the problem of classification in partially labeled networks (a.k.a. within-network classification) where observed class labels are sparse. Techniques for statistical re...
Brian Gallagher, Hanghang Tong, Tina Eliassi-Rad, ...