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  • 标题:Intentional Kernel Functions
  • 本地全文:下载
  • 作者:Koichiro Doi ; Tetsuya Yamashita ; Takayuki Tanaka
  • 期刊名称:人工知能学会論文誌
  • 印刷版ISSN:1346-0714
  • 电子版ISSN:1346-8030
  • 出版年度:2008
  • 卷号:23
  • 期号:3
  • 页码:185-192
  • DOI:10.1527/tjsai.23.185
  • 出版社:The Japanese Society for Artificial Intelligence
  • 摘要:We present the intentional kernel as a new class of kernel functions for structured data. The class is highly contrasted to the convolution kernel, that is a typical class of kernel functions. That is, the convolution kernel is defined with sub-structures, while the intentional kernel is based on derivations constracting structures. We show instances of the intentional kernel for boolean functions, first-order terms, context sensitive languages, and RNA sequences. We also show some properties of the intentional kernel, and discuss the difference between the intentional kernel and the convolution kernel.
  • 关键词:kernel function ; structured data ; intentional kernel
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