A Chinese question classification using one-vs-one method as a learning tool

Question classification plays an important role in the question answering system and the errors of question classification will probably result in the failure of question answering. Thus, how to enhance the accuracy is an open question. In order to enhance the accuracies of the Chinese question classification, this paper extends one-against-one method based on SVMs to resolve the problems. The results show the good performance of the algorithm for Chinese question classification problems.

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