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FLAIRS
2004
15 years 5 months ago
Case-Based Bayesian Network Classifiers
We propose a new approach for learning Bayesian classifiers from data. Although it relies on traditional Bayesian network (BN) learning algorithms, the effectiveness of our approa...
Eugene Santos, Ahmed Huessin
IADIS
2003
15 years 5 months ago
Versioning of E-Learning Objects Enabling Flexible Reuse
One promise that has always been made in the field of e-learning is the possibility to create and deliver learning material that is adaptable to individual learners. Realising thi...
Wolfgang Theilmann, Michael Altenhofen
COLING
2000
15 years 5 months ago
Word Sense Disambiguation of Adjectives Using Probabilistic Networks
In this paper, word sense dismnbiguation (WSD) accuracy achievable by a probabilistic classifier, using very milfimal training sets, is investigated. \Ve made the assuml)tiou that...
Gerald Chao, Michael G. Dyer
AAAI
1996
15 years 5 months ago
Dynamically Sequencing an Animated Pedagogical Agent
One of the most promising opportunities introduced by rapid advances in knowledge-based learning environments and multimedia technologies is the possibility of creating animated p...
Brian A. Stone, James C. Lester
PR
2006
147views more  PR 2006»
15 years 3 months ago
Robust locally linear embedding
In the past few years, some nonlinear dimensionality reduction (NLDR) or nonlinear manifold learning methods have aroused a great deal of interest in the machine learning communit...
Hong Chang, Dit-Yan Yeung