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AIED
2007
Springer
15 years 4 months ago
Comparing Linguistic Features for Modeling Learning in Computer Tutoring
We compare the relative utility of different automatically computable linguistic feature sets for modeling student learning in computer dialogue tutoring. We use the PARADISE frame...
Katherine Forbes-Riley, Diane J. Litman, Amruta Pu...
ICTAI
2010
IEEE
14 years 7 months ago
Unsupervised Greedy Learning of Finite Mixture Models
This work deals with a new technique for the estimation of the parameters and number of components in a finite mixture model. The learning procedure is performed by means of a expe...
Nicola Greggio, Alexandre Bernardino, Cecilia Lasc...
EMNLP
2008
14 years 11 months ago
Phrase Translation Probabilities with ITG Priors and Smoothing as Learning Objective
The conditional phrase translation probabilities constitute the principal components of phrase-based machine translation systems. These probabilities are estimated using a heurist...
Markos Mylonakis, Khalil Sima'an
ITS
1992
Springer
152views Multimedia» more  ITS 1992»
15 years 1 months ago
People Power: A Human-Computer Collaborative Learning System
Abstract. This paper reports our research work in the new field of humancomputer collaborative learning (HCCL). The general architecture of an HCCL is defined. An HCCL system, call...
Pierre Dillenbourg, John A. Self
IJAR
2006
89views more  IJAR 2006»
14 years 10 months ago
Learning probabilistic decision graphs
Probabilistic decision graphs (PDGs) are a representation language for probability distributions based on binary decision diagrams. PDGs can encode (context-specific) independence...
Manfred Jaeger, Jens D. Nielsen, Tomi Silander