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ICDCSW
2007
IEEE
15 years 4 months ago
Event Stream Processing with Out-of-Order Data Arrival
Complex event processing has become increasingly important in modern applications, ranging from supply chain management for RFID tracking to real-time intrusion detection. The goa...
Ming Li, Mo Liu, Luping Ding, Elke A. Rundensteine...
52
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CHI
2009
ACM
15 years 10 months ago
Using temporal patterns (t-patterns) to derive stress factors of routine tasks
We describe the use of a statistical technique called Tpattern analysis to derive and characterize the routineness of tasks. T-patterns provide significant advantages over traditi...
Oliver Brdiczka, Norman Makoto Su, Bo Begole
KDD
2009
ACM
224views Data Mining» more  KDD 2009»
15 years 2 months ago
Issues in evaluation of stream learning algorithms
Learning from data streams is a research area of increasing importance. Nowadays, several stream learning algorithms have been developed. Most of them learn decision models that c...
João Gama, Raquel Sebastião, Pedro P...
ECOI
2010
117views more  ECOI 2010»
14 years 9 months ago
Ensemble extraction for classification and detection of bird species
Advances in technology have enabled new approaches for sensing the environment and collecting data about the world. Once collected, sensor readings can be assembled into data stre...
Eric P. Kasten, Philip K. McKinley, Stuart H. Gage
CIKM
2009
Springer
15 years 28 days ago
Mining data streams with periodically changing distributions
Dynamic data streams are those whose underlying distribution changes over time. They occur in a number of application domains, and mining them is important for these applications....
Yingying Tao, M. Tamer Özsu