Richard Wicentowski (2004): Multilingual Noise-Robust Supervised Morphological Analysis using the WordFrame Model

• 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.

• R. Wicentowski, 2002, PhD thesis

• Robustness of the algorithm in noisy conditions
• Evaluation on many different languages

• Doesn't do morphological analysis, only lemmatization
• Experiments done only on verbs
• The paper doesn't say, what option the algorithm selects if there are more possible correct results
• The algorithm only uses features based only on the word itself, it doesn't use context
• With information given in this paper, we wouldn't be able to create a program to review the results

• Does the term point of prefixation mean the same as the term morpheme boundary?

Written by Martin Kirschner