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courses:rg:multilingual-noise-robust-supervised-morphological-analysis-using-the-wordframe-model [2011/01/07 18:32]
kirschner 		courses:rg:multilingual-noise-robust-supervised-morphological-analysis-using-the-wordframe-model [2011/01/07 18:38]
kirschner
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     * A combination of both methods gives even better results.     * A combination of both methods gives even better results.
   * The results are evaulated on 30 different languages with median accuracy 97.5%   * The results are evaulated on 30 different languages with median accuracy 97.5%
-  * WordFrame model algorithm+  * The WordFrame model algorithm trains well on noisy data, therefore it can be used in co-training with unsupervised methods.
      
  
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 ===== What do we like about the paper ===== ===== What do we like about the paper =====
-  * +  * Robustness of the algorithm in noisy conditions 
 +  * Evaluation on many different languages
  
 ===== What do we dislike about the paper ===== ===== What do we dislike about the paper =====

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