Fast Methods for Kernel-Based Text Analysis

  title={Fast Methods for Kernel-Based Text Analysis},
  author={Taku Kudo and Yuji Matsumoto},
Kernel-based learning (e.g., Support Vector Machines) has been successfully applied to many hard problems in Natural Language Processing (NLP). In NLP, although feature combinations are crucial to improving performance, they are heuristically selected. Kernel methods change this situation. The merit of the kernel methods is that effective feature combination is implicitly expanded without loss of generality and increasing the computational costs. Kernel-based text analysis shows an excellent… CONTINUE READING
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