We often meet the tree decomposition task in the tree kernel computing. And tree decomposition tends to vary under different tree mapping constraint.

In this paper, we first introduce the general tree decomposition function, and compare the three variants of the function corresponding to different tree ...

We propose an approach whereby some computations for smaller trees are cached, which speeds up considerably the computation of all these tree kernels. We ...

Jul 22, 2020 · In this paper we propose a method of representing an event sequence by a burst tree, which is then decomposed into a set of IETs and an ordinal burst tree.

As mentioned above later in this chapter we will give a more efficient method for computing the p-spectrum kernel. This will be based on a tree- like data ...

Bibliographic details on Decomposition Method for Tree Kernels.

Tree kernels. We now discuss similarity measures on more structured objects. For trees Collins and Duffy [31] propose a decomposition method which maps a.

To handle problems created by large data sets, we propose a method that uses a decision tree to decompose a given data space and trains SVMs on the ...

Sep 3, 2024 · The burst-tree decomposition method was recently introduced to reveal higher-order temporal correlations in time series in a form of an ...

For plane digraphs we introduce a new parameter which we call the kernel number. For a plane digraph the kernel number is the minimum number.