… kernel, we present a new string kernel (sequencesimilarity kernel), the spectrum kernel, for
… , we introduce a simple string kernel, which we call the spectrum kernel, on the input space X …

… of elements (strings, graphs, images) an ‘inner product’ in a feature space. For such kernels,
it … We examine the use of a kernel method based on string alignment for text categorization …

… In this chapter we study string kernels that can be computed in linear time wrt … string kernels
that are particularly well suited for sequence analysis tasks (section 4.2). We study kernels …

… ● Sequence kernels Sequence kernel is a kind of string kernel in … A protein or gene sequence
is considered as a string defined … We summarize the existing string kernel method and its …

… We introduce a novel kernel for comparing two text documents. The kernel is an inner product
in … In this paper we examine the use of a kernel method based on string alignment for text …

… of k-mer based string kernels related to the recently presented mismatch kernel and designed
for use … These new kernels – restricted gappy kernels, substitution kernels, and wildcard …

… the basic definition of the string and tree kernels used in this … can be used to compute string
kernels efficiently. Sections 5.4 … of kernels we will be studying are defined by String kernel …

… We introduce a class of string kernels, called mismatch kernels, for use with support
vector machines (SVMs) in a discriminative approach to the protein classification problem …

… For the case of profile string kernels, we show how we can use the trained SVM classifiers
to define positional scores along the protein profiles that define a smoothed contribution to the …

… More precisely, we treated texts as just sequences of symbols (strings) and used string
kernels in conjunction with different kernel-based learning methods: supervised and …