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AAAI
2012
13 years 6 days ago
Discovering Constraints for Inductive Process Modeling
Scientists use two forms of knowledge in the construction of explanatory models: generalized entities and processes that relate them; and constraints that specify acceptable combi...
Ljupco Todorovski, Will Bridewell, Pat Langley
ICASSP
2010
IEEE
14 years 4 months ago
Unsupervised knowledge acquisition for Extracting Named Entities from speech
This paper presents a Named Entity Recognition (NER) method dedicated to process speech transcriptions. The main principle behind this method is to collect in an unsupervised way ...
Frédéric Béchet, Eric Charton
ECML
2006
Springer
15 years 1 months ago
Learning Process Models with Missing Data
Abstract. In this paper, we review the task of inductive process modeling, which uses domain knowledge to compose explanatory models of continuous dynamic systems. Next we discuss ...
Will Bridewell, Pat Langley, Steve Racunas, Stuart...
NC
2010
150views Neural Networks» more  NC 2010»
14 years 8 months ago
Deterministic and stochastic P systems for modelling cellular processes
This paper presents two approaches based on metabolic and stochastic P systems, together with their associated analysis methods, for modelling biological systems and illustrates th...
Marian Gheorghe, Vincenzo Manca, Francisco Jos&eac...
AEI
2005
102views more  AEI 2005»
14 years 9 months ago
Manufacturing planning and predictive process model integration using software agents
Intelligent agents provide a means to integrate various manufacturing software applications. The agents are typically executed in a computer-based collaborative environment, refer...
Shaw C. Feng, Keith A. Stouffer, Kevin K. Jurrens