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» Improving Statistical Word Alignment with Ensemble Methods
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ACL
2012
11 years 10 months ago
Improving the IBM Alignment Models Using Variational Bayes
Bayesian approaches have been shown to reduce the amount of overfitting that occurs when running the EM algorithm, by placing prior probabilities on the model parameters. We appl...
Darcey Riley, Daniel Gildea
AI
2009
Springer
14 years 2 months ago
Enhancing the Bilingual Concordancer TransSearch with Word-Level Alignment
Despite the impressive amount of recent studies devoted to improving the state of the art of Machine Translation (MT), Computer Assisted Translation (CAT) tools remain the preferre...
Julien Bourdaillet, Stéphane Huet, Fabrizio...
SDM
2008
SIAM
177views Data Mining» more  SDM 2008»
13 years 9 months ago
Cluster Ensemble Selection
This paper studies the ensemble selection problem for unsupervised learning. Given a large library of different clustering solutions, our goal is to select a subset of solutions t...
Xiaoli Z. Fern, Wei Lin
IBPRIA
2003
Springer
14 years 20 days ago
Combining Phrase-Based and Template-Based Alignment Models in Statistical Translation
In statistical machine translation, single-word based models have an important deficiency; they do not take contextual information into account for the translation decision. A poss...
Jesús Tomás, Francisco Casacuberta
COLING
2008
13 years 9 months ago
Improving Alignments for Better Confusion Networks for Combining Machine Translation Systems
The state-of-the-art system combination method for machine translation (MT) is the word-based combination using confusion networks. One of the crucial steps in confusion network d...
Necip Fazil Ayan, Jing Zheng, Wen Wang