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ICML
2005
IEEE
16 years 8 months ago
Exploiting syntactic, semantic and lexical regularities in language modeling via directed Markov random fields
We present a directed Markov random field (MRF) model that combines n-gram models, probabilistic context free grammars (PCFGs) and probabilistic latent semantic analysis (PLSA) fo...
Shaojun Wang, Shaomin Wang, Russell Greiner, Dale ...
SIGSOFT
2009
ACM
16 years 7 months ago
Probabilistic environments in the quantitative analysis of (non-probabilistic) behaviour models
System specifications have long been expressed through automata-based languages, enabling verification techniques such as model checking. These verification techniques can assess ...
Esteban Pavese, Sebastián Uchitel, Ví...
ECOOP
2009
Springer
16 years 7 months ago
COPE - Automating Coupled Evolution of Metamodels and Models
Model-based development promises to increase productivity by offering modeling languages tailored to a specific domain. Such modeling languages are typically defined by a metamodel...
Elmar Jürgens, Markus Herrmannsdoerfer, Sebas...
KDD
2007
ACM
122views Data Mining» more  KDD 2007»
16 years 7 months ago
Expertise modeling for matching papers with reviewers
An essential part of an expert-finding task, such as matching reviewers to submitted papers, is the ability to model the expertise of a person based on documents. We evaluate seve...
David M. Mimno, Andrew McCallum
CHI
2007
ACM
16 years 7 months ago
Toolkit support for developing and deploying sensor-based statistical models of human situations
Sensor-based statistical models promise to support a variety of advances in human-computer interaction, but building applications that use them is currently difficult and potentia...
James Fogarty, Scott E. Hudson
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