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ML
2006
ACM
131views Machine Learning» more  ML 2006»
15 years 3 months ago
Markov logic networks
We propose a simple approach to combining first-order logic and probabilistic graphical models in a single representation. A Markov logic network (MLN) is a first-order knowledge b...
Matthew Richardson, Pedro Domingos
JSW
2007
126views more  JSW 2007»
15 years 3 months ago
On Remote and Virtual Experiments in eLearning
— The science of physics is based on theories and models as well as experiments: the former structure relations and simplify reality to a degree such that predictions on physical...
Sabina Jeschke, Harald Scheel, Thomas Richter, Chr...
JOT
2010
124views more  JOT 2010»
15 years 2 months ago
Improving Learning Object Reuse Through OOD: A Theory of Learning Objects
The concept of a learning object (LO) has spread quickly without a very specific universal definition, and though born originally from the idea of object oriented design, with a ...
Claudine A. Allen, Ezra K. Mugisa
RSKT
2010
Springer
15 years 2 months ago
Naive Bayesian Rough Sets
A naive Bayesian classifier is a probabilistic classifier based on Bayesian decision theory with naive independence assumptions, which is often used for ranking or constructing a...
Yiyu Yao, Bing Zhou
ERCIMDL
2010
Springer
130views Education» more  ERCIMDL 2010»
15 years 2 months ago
LIFE-SHARE Project: Developing a Digitisation Strategy Toolkit
This poster will outline the Digitisation Strategy Toolkit created as part of the LIFE-SHARE project. The toolkit is based on the lifecycle model created by the LIFE project and ex...
Beccy Shipman, Matthew Herring, Ned Potter, Bo Mid...