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论文类型：会议论文

发表时间：2005-05-30

收录刊物：EI

卷号：3497

期号：II

页面范围：246-250

摘要：This paper presents a method of processing Chinese syntactic category ambiguity with support vector machines (SVMs): extracting the word itself, candidate part-of-speech (POS) tags, the pair of candidate POS tags and their probability and context information as the features of the word vector. A training set is established. The machine learning models of disambiguation based on support vector machines are obtained using polynomial kernel functions. The testing results show that this method is efficient. The paper also gives the results obtained with neural networks for comparison. © Springer-Verlag Berlin Heidelberg 2005.