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» Modeling word burstiness using the Dirichlet distribution
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COLING
2010
14 years 6 months ago
Nonparametric Word Segmentation for Machine Translation
We present an unsupervised word segmentation model for machine translation. The model uses existing monolingual segmentation techniques and models the joint distribution over sour...
ThuyLinh Nguyen, Stephan Vogel, Noah A. Smith
71
Voted
LREC
2008
84views Education» more  LREC 2008»
15 years 1 months ago
Using the Complexity of the Distribution of Lexical Elements as a Feature in Authorship Attribution
Traditional Authorship Attribution models extract normalized counts of lexical elements such as nouns, common words and punctuation and use these normalized counts or ratios as fe...
Leanne Spracklin, Diana Inkpen, Amiya Nayak
102
Voted
ENTCS
2011
130views more  ENTCS 2011»
14 years 6 months ago
Bell States and Negative Sentences in the Distributed Model of Meaning
We use Bell states to provide compositional distributed meaning for negative sentences of English. The lexical meaning of each word of the sentence is a context vector obtained wi...
Anne Preller, Mehrnoosh Sadrzadeh
NIPS
2008
15 years 1 months ago
Unsupervised Learning of Visual Sense Models for Polysemous Words
Polysemy is a problem for methods that exploit image search engines to build object category models. Existing unsupervised approaches do not take word sense into consideration. We...
Kate Saenko, Trevor Darrell
97
Voted
CVPR
2003
IEEE
16 years 1 months ago
A Bayesian Framework for Fusing Multiple Word Knowledge Models in Videotext Recognition
Videotext recognition is challenging due to low resolution, diverse fonts/styles, and cluttered background. Past methods enhanced recognition by using multiple frame averaging, im...
DongQing Zhang, Shih-Fu Chang