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• W2016790987 abstract "Tree kernels proposed in the literature rarely use information about the relative location of the substructures within a tree. As this type of information is orthogonal to the one commonly exploited by tree kernels, the two can be combined to enhance state-of-the-art accuracy of tree kernels. In this brief, our attention is focused on subtree kernels. We describe an efficient algorithm for injecting positional information into a tree kernel and present ways to enlarge its feature space without affecting its worst case complexity. The experimental results on several benchmark datasets are presented showing that our method is able to reach state-of-the-art performances, obtaining in some cases better performance than computationally more demanding tree kernels." @default.
• W2016790987 created "2016-06-24" @default.
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• W2016790987 date "2015-05-01" @default.
• W2016790987 modified "2023-09-25" @default.
• W2016790987 title "An Efficient Topological Distance-Based Tree Kernel" @default.
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• W2016790987 doi "https://doi.org/10.1109/tnnls.2014.2329331" @default.
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