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» Learning probabilistic models of the Web
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KDD
2004
ACM
209views Data Mining» more  KDD 2004»
16 years 5 months ago
Tracking dynamics of topic trends using a finite mixture model
In a wide range of business areas dealing with text data streams, including CRM, knowledge management, and Web monitoring services, it is an important issue to discover topic tren...
Satoshi Morinaga, Kenji Yamanishi
ICCV
2001
IEEE
16 years 7 months ago
Human Tracking with Mixtures of Trees
Tree-structured probabilistic models admit simple, fast inference. However, they are not well suited to phenomena such as occlusion, where multiple components of an object may dis...
Sergey Ioffe, David A. Forsyth
KES
2007
Springer
15 years 11 months ago
Predictive and Contextual Feature Separation for Bayesian Metanetworks
Bayesian Networks are proven to be a comprehensive model to describe causal relationships among domain attributes with probabilistic measure of conditional dependency. However, dep...
Vagan Y. Terziyan
147
Voted
SIGIR
2006
ACM
15 years 11 months ago
Text clustering with extended user feedback
Text clustering is most commonly treated as a fully automated task without user feedback. However, a variety of researchers have explored mixed-initiative clustering methods which...
Yifen Huang, Tom M. Mitchell
ICCV
2005
IEEE
15 years 11 months ago
Behaviour Understanding in Video: A Combined Method
In this paper we develop a system for human behaviour recognition in video sequences. Human behaviour is modelled as a stochastic sequence of actions. Actions are described by a f...
Neil Robertson, Ian D. Reid