This is an old revision of the document!
Table of Contents
Multilingual Noise-Robust Supervised Morphological Analysis using the WordFrame Model
Richard Wicentowski (2004): Multilingual Noise-Robust Supervised Morphological Analysis using the WordFrame Model
Comments
- In this paper the author presents a new supervized method for lemmatization, called WordFrame model.
- 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
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
Written by Martin Kirschner