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In this paper, we present a novel recognition algorithm which is based on RB K-means and Hierarchical SVM (Support Vector Machines). Firstly, we pre-classify imposter samples by RB K-means. Secondly, the Linear SVM is applied to the primary classification. Finally, we use the Non-linear SVM for the classification. Our experiment demonstrates that our algorithm with RBF kernel is feasible and effective...
New words bring more challenges into Chinese word segmentation. This paper presents a SVM-based hybrid pattern for new word discovery, trying to integrate the advantages of the statistics-based method and the rule-based method to improve the performance of the new word discovery. In the statistics module, new words discovery is defined as a binary classification problem, in which we considered the...
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