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» Using Clustering Methods for Discovering Event Structures
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ESANN
2006
13 years 10 months ago
Data topology visualization for the Self-Organizing Map
The Self-Organizing map (SOM), a powerful method for data mining and cluster extraction, is very useful for processing data of high dimensionality and complexity. Visualization met...
Kadim Tasdemir, Erzsébet Merényi
DSN
2005
IEEE
14 years 2 months ago
TIBFIT: Trust Index Based Fault Tolerance for Arbitrary Data Faults in Sensor Networks
Since sensor data gathering is the primary functionality of sensor networks, it is important to provide a fault tolerant method for reasoning about sensed events in the face of ar...
Mark D. Krasniewski, Padma Varadharajan, Bryan Rab...
WSDM
2012
ACM
207views Data Mining» more  WSDM 2012»
12 years 4 months ago
Sequence clustering and labeling for unsupervised query intent discovery
One popular form of semantic search observed in several modern search engines is to recognize query patterns that trigger instant answers or domain-specific search, producing sem...
Jackie Chi Kit Cheung, Xiao Li
IDA
2003
Springer
14 years 1 months ago
A Semi-supervised Method for Learning the Structure of Robot Environment Interactions
For a mobile robot to act autonomously, it must be able to construct a model of its interaction with the environment. Oates et al. developed an unsupervised learning method that pr...
Axel Großmann, Matthias Wendt, Jeremy Wyatt
IVC
2002
192views more  IVC 2002»
13 years 8 months ago
Understanding visual behaviour
Modelling events is one of the key problems in dynamic scene analysis when salient and autonomous visual changes occuring in a scene need to be characterised effectively as meanin...
Shaogang Gong, Hilary Buxton