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» Generation that Exploits Corpus-Based Statistical Knowledge
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ICASSP
2010
IEEE
12 years 11 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
CLEF
2008
Springer
13 years 6 months ago
Exploiting Term Co-occurrence for Enhancing Automated Image Annotation
This paper describes an application of statistical co-occurrence techniques that built on top of a probabilistic image annotation framework is able to increase the precision of an ...
Ainhoa Llorente, Simon E. Overell, Haiming Liu 000...
UAIS
2008
155views more  UAIS 2008»
13 years 4 months ago
Adaptive course generation through learning styles representation
This paper presents an approach to automatic course generation and student modeling. The method has been developed during the European funded projects Diogene and Intraserv, focuse...
Enver Sangineto, Nicola Capuano, Matteo Gaeta, Ale...
EMNLP
2008
13 years 6 months ago
Modeling Annotators: A Generative Approach to Learning from Annotator Rationales
A human annotator can provide hints to a machine learner by highlighting contextual "rationales" for each of his or her annotations (Zaidan et al., 2007). How can one ex...
Omar Zaidan, Jason Eisner