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IJAR
2006
118views more  IJAR 2006»
15 years 6 months ago
Learning Bayesian network parameters under order constraints
We consider the problem of learning the parameters of a Bayesian network from data, while taking into account prior knowledge about the signs of influences between variables. Such...
A. J. Feelders, Linda C. van der Gaag
SSPR
1998
Springer
15 years 10 months ago
Multi-interval Discretization Methods for Decision Tree Learning
Properly addressing the discretization process of continuos valued features is an important problem during decision tree learning. This paper describes four multi-interval discreti...
Petra Perner, Sascha Trautzsch
COLING
2010
15 years 1 months ago
Grouping Product Features Using Semi-Supervised Learning with Soft-Constraints
In opinion mining of product reviews, one often wants to produce a summary of opinions based on product features/attributes. However, for the same feature, people can express it w...
Zhongwu Zhai, Bing Liu, Hua Xu, Peifa Jia
FLAIRS
2006
15 years 8 months ago
Supporting Systematic Usage of Context in Web Applications
Context can be seen as a paradigm aiming to improve user interaction with software. For Web applications in particular, the issues of content explosion and technological constrain...
J. Wolfgang Kaltz, Jürgen Ziegler
SIAMSC
2010
119views more  SIAMSC 2010»
15 years 5 months ago
An Entropy Adjoint Approach to Mesh Refinement
This work presents a mesh refinement indicator based on entropy variables, with an application to the compressible Navier-Stokes equations. The entropy variables are shown to sati...
Krzysztof J. Fidkowski, Philip L. Roe