Differences
This shows you the differences between two versions of the page.
Both sides previous revision Previous revision Next revision | Previous revision Next revision Both sides next revision | ||
courses:rg:multilingual-noise-robust-supervised-morphological-analysis-using-the-wordframe-model [2011/01/07 17:55] kirschner |
courses:rg:multilingual-noise-robust-supervised-morphological-analysis-using-the-wordframe-model [2011/01/07 18:51] kirschner |
||
---|---|---|---|
Line 5: | Line 5: | ||
===== Comments ===== | ===== Comments ===== | ||
- | * | + | * In this paper the author presents a new supervized method for lemmatization, |
+ | * This new method is compared to existing End-Of-String method and is proven better in most of the cases. | ||
+ | * A combination of both methods gives even better results. | ||
+ | * The results are evaulated on 30 different languages with median accuracy 97.5% | ||
+ | * The WordFrame model algorithm trains well on noisy data, therefore it can be used in co-training with unsupervised methods. | ||
| | ||
+ | |||
===== Suggested Additional Reading ===== | ===== Suggested Additional Reading ===== | ||
* [[http:// | * [[http:// | ||
Line 15: | Line 20: | ||
===== 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 ===== | ||
- | * | + | * Doesn' |
+ | * Experiments done only on verbs | ||
+ | * The paper doesn' | ||
+ | * The algorithm only uses features based only on the word itself, it doesn' | ||
+ | * With information given in this paper, we wouldn' | ||
+ | |||
+ | ===== Questions ===== | ||
+ | * Does the term //point of prefixation// | ||
Written by Martin Kirschner | Written by Martin Kirschner |