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» Word Importance Discrimination Using Context Information
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ICCV
2009
IEEE
16 years 2 months ago
TagProp: Discriminative Metric Learning in Nearest Neighbor Models for Image Auto-Annotation
Image auto-annotation is an important open problem in computer vision. For this task we propose TagProp, a discriminatively trained nearest neighbor model. Tags of test images a...
Matthieu Guillaumin, Thomas Mensink, Jakob Verbeek...
LREC
2008
159views Education» more  LREC 2008»
14 years 11 months ago
Evaluation of Context-Dependent Phrasal Translation Lexicons for Statistical Machine Translation
We present new direct data analysis showing that dynamically-built context-dependent phrasal translation lexicons are more useful resources for phrase-based statistical machine tr...
Marine Carpuat, Dekai Wu
DAIS
2007
14 years 11 months ago
Scalable Processing of Context Information with COSMOS
Abstract. Ubiquitous computing environments are characterised by a high number of heterogenous devices that generate a huge amount of context data. These data are used, for example...
Denis Conan, Romain Rouvoy, Lionel Seinturier
CICLING
2006
Springer
15 years 1 months ago
Verb Sense Disambiguation Using Support Vector Machines: Impact of WordNet-Extracted Features
The disambiguation of verbs is usually considered to be more difficult with respect to other part-of-speech categories. This is due both to the high polysemy of verbs compared with...
Davide Buscaldi, Paolo Rosso, Ferran Pla, Encarna ...
ICPR
2010
IEEE
14 years 7 months ago
Word Clustering Using PLSA Enhanced with Long Distance Bigrams
Probabilistic latent semantic analysis is enhanced with long distance bigram models in order to improve word clustering. The long distance bigram probabilities and the interpolate...
Nikoletta Bassiou, Constantine Kotropoulos