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AUSDM
2007
Springer
102views Data Mining» more  AUSDM 2007»
14 years 3 months ago
Determining Termhood for Learning Domain Ontologies in a Probabilistic Framework
Many existing techniques for term extraction are heuristically-motivated and criticised as ad-hoc. The definitions and assumptions critical to set the boundary for the effective...
Wilson Wong, Wei Liu, Mohammed Bennamoun
ICALT
2006
IEEE
14 years 3 months ago
Automatic Generation of Metadata for Learning Objects
Proper reuse of learning objects depends both on the amount and quality of attached semantic metadata such as “learning objective”', “related concept”, etc. Manually ...
Paramjeet Singh Saini, Marco Ronchetti, Diego Sona
ML
2006
ACM
121views Machine Learning» more  ML 2006»
13 years 9 months ago
Model-based transductive learning of the kernel matrix
This paper addresses the problem of transductive learning of the kernel matrix from a probabilistic perspective. We define the kernel matrix as a Wishart process prior and construc...
Zhihua Zhang, James T. Kwok, Dit-Yan Yeung
FLAIRS
2006
13 years 10 months ago
Decomposing Local Probability Distributions in Bayesian Networks for Improved Inference and Parameter Learning
A major difficulty in building Bayesian network models is the size of conditional probability tables, which grow exponentially in the number of parents. One way of dealing with th...
Adam Zagorecki, Mark Voortman, Marek J. Druzdzel
ICMLA
2010
13 years 7 months ago
A Probabilistic Graphical Model of Quantum Systems
Quantum systems are promising candidates of future computing and information processing devices. In a large system, information about the quantum states and processes may be incomp...
Chen-Hsiang Yeang