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ACL
2012
11 years 7 months ago
Labeling Documents with Timestamps: Learning from their Time Expressions
Temporal reasoners for document understanding typically assume that a document’s creation date is known. Algorithms to ground relative time expressions and order events often re...
Nathanael Chambers
SIGIR
2008
ACM
13 years 5 months ago
Learning from labeled features using generalized expectation criteria
It is difficult to apply machine learning to new domains because often we lack labeled problem instances. In this paper, we provide a solution to this problem that leverages domai...
Gregory Druck, Gideon S. Mann, Andrew McCallum
EMNLP
2010
13 years 3 months ago
WikiWars: A New Corpus for Research on Temporal Expressions
The reliable extraction of knowledge from text requires an appropriate treatment of the time at which reported events take place. Unfortunately, there are very few annotated data ...
Pawel P. Mazur, Robert Dale
WWW
2008
ACM
14 years 5 months ago
Learning deterministic regular expressions for the inference of schemas from XML data
Inferring an appropriate DTD or XML Schema Definition (XSD) for a given collection of XML documents essentially reduces to learning deterministic regular expressions from sets of ...
Geert Jan Bex, Wouter Gelade, Frank Neven, Stijn V...
ICCV
2005
IEEE
13 years 10 months ago
Learning Non-Generative Grammatical Models for Document Analysis
— We present a general approach for the hierarchical segmentation and labeling of document layout structures. This approach models document layout as a grammar and performs a glo...
Michael Shilman, Percy Liang, Paul A. Viola