Transactions of the Japanese Society for Artificial Intelligence
Online ISSN : 1346-8030
Print ISSN : 1346-0714
ISSN-L : 1346-0714
Technical Papers
Design and Analysis of Convolution Kernels for Tree-Structured Data
Hisashi KashimaHiroshi SakamotoTeruo Koyanagi
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2006 Volume 21 Issue 1 Pages 113-121

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Abstract
We introduce a new convolution kernel for labeled ordered trees with arbitrary subgraph features, and an efficient algorithm for computing the kernel with the same time complexity as that of the parse tree kernel. The proposed kernel is extended to allow mutations of labels and structures without increasing the order of computation time. Moreover, as a limit of generalization of the tree kernels, we show a hardness result in computing kernels for unordered rooted labeled trees with arbitrary subgraph features.
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© 2006 JSAI (The Japanese Society for Artificial Intelligence)
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