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» Learning Causal Models of Relational Domains
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KDD
2005
ACM
86views Data Mining» more  KDD 2005»
16 years 2 months ago
Probabilistic workflow mining
In several organizations, it has become increasingly popular to document and log the steps that makeup a typical business process. In some situations, a normative workflow model o...
Ricardo Silva, Jiji Zhang, James G. Shanahan
ML
2008
ACM
100views Machine Learning» more  ML 2008»
15 years 1 months ago
Generalized ordering-search for learning directed probabilistic logical models
Abstract. Recently, there has been an increasing interest in directed probabilistic logical models and a variety of languages for describing such models has been proposed. Although...
Jan Ramon, Tom Croonenborghs, Daan Fierens, Hendri...
NAACL
2010
14 years 11 months ago
Automatic Domain Adaptation for Parsing
Current statistical parsers tend to perform well only on their training domain and nearby genres. While strong performance on a few related domains is sufficient for many situatio...
David McClosky, Eugene Charniak, Mark Johnson
ACL
2009
14 years 11 months ago
Distant supervision for relation extraction without labeled data
Modern models of relation extraction for tasks like ACE are based on supervised learning of relations from small hand-labeled corpora. We investigate an alternative paradigm that ...
Mike Mintz, Steven Bills, Rion Snow, Daniel Jurafs...
JAIR
2010
145views more  JAIR 2010»
15 years 5 days ago
Planning with Noisy Probabilistic Relational Rules
Noisy probabilistic relational rules are a promising world model representation for several reasons. They are compact and generalize over world instantiations. They are usually in...
Tobias Lang, Marc Toussaint