Use of support vector learning for chunk identification
Taku Kudoh, Yūji Matsumoto · 2000
In this paper, we explore the use of Support Vector Machines (SVMs) for CoNLL-2000 shared task, chunk identification. SVMs are so-called large margin classifiers and are well-known as their good generalization performance. We investigate how SVMs with a very large number of features perform with the classification task of chunk labelling.