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» Phenomenal Data Mining: From Data to Phenomena
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DMSN
2007
ACM
14 years 1 months ago
Declarative temporal data models for sensor-driven query processing
Many sensor network applications monitor continuous phenomena by sampling, and fit time-varying models that capture the phenomena's behaviors. We introduce Pulse, a framework...
Yanif Ahmad, Ugur Çetintemel
SDM
2007
SIAM
198views Data Mining» more  SDM 2007»
13 years 10 months ago
Learning from Time-Changing Data with Adaptive Windowing
We present a new approach for dealing with distribution change and concept drift when learning from data sequences that may vary with time. We use sliding windows whose size, inst...
Albert Bifet, Ricard Gavaldà
KDD
1999
ACM
104views Data Mining» more  KDD 1999»
14 years 1 months ago
Learning Rules from Distributed Data
In this paper a concern about the accuracy (as a function of parallelism) of a certain class of distributed learning algorithms is raised, and one proposed improvement is illustrat...
Lawrence O. Hall, Nitesh V. Chawla, Kevin W. Bowye...
SIGMOD
2010
ACM
217views Database» more  SIGMOD 2010»
14 years 1 months ago
Mining knowledge from databases: an information network analysis approach
Most people consider a database is merely a data repository that supports data storage and retrieval. Actually, a database contains rich, inter-related, multi-typed data and infor...
Jiawei Han, Yizhou Sun, Xifeng Yan, Philip S. Yu
TCS
2008
13 years 9 months ago
Efficient corona training protocols for sensor networks
Phenomenal advances in nano-technology and packaging have made it possible to develop miniaturized low-power devices that integrate sensing, special-purpose computing, and wireles...
Alan A. Bertossi, Stephan Olariu, Maria Cristina P...