文章基本信息

标题：A Spectrum Tree Kernel
本地全文：下载
作者：Tetsuji Kuboyama ; Kouichi Hirata ; Hisashi Kashima 等
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：2007
卷号：22
期号：2
页码：140-147
DOI：10.1527/tjsai.22.140
出版社：The Japanese Society for Artificial Intelligence
摘要：Learning from tree-structured data has received increasing interest with the rapid growth of tree-encodable data in the World Wide Web, in biology, and in other areas. Our kernel function measures the similarity between two trees by counting the number of shared sub-patterns called tree q -grams, and runs, in effect, in linear time with respect to the number of tree nodes. We apply our kernel function with a support vector machine (SVM) to classify biological data, the glycans of several blood components. The experimental results show that our kernel function performs as well as one exclusively tailored to glycan properties.
关键词：tree kernels ; glycans ; spectrum kernels ; kernel methods ; structured data