SVM model tampering and anchored learning: a case study in Hebrew NP chunking Academic Article uri icon


  • Abstract We study the issue of porting a known NLP method to a language with little existing NLP resources, specifically Hebrew SVM-based chunking. We introduce two SVM-based methods–Model Tampering and Anchored Learning. These allow fine grained analysis of the learned SVM models, which provides guidance to identify errors in the training corpus, distinguish the role and interaction of lexical features and eventually construct a model with~ 10% error reduction. The resulting chunker is shown to be robust in the presence of noise …

publication date

  • June 23, 2007