Skip to main content

String Kernel

  • Reference work entry
  • First Online:
Encyclopedia of Machine Learning and Data Mining
  • 107 Accesses

A string kernel is a function from any of various families of kernel functions (see kernel methods) that operate over strings and sequences. The most typical example is as follows. Suppose that we are dealing with strings over a finite alphabet Σ. Given a string a = a1a2… a n ∈ Σ∗, we say that a substring p = p1p2… p k occurs in a on positions i1i2… i k iff 1 ≤ i1 < i2 < … < i k ≤ n and a ij = p j for all j = 1, …, k. We define the weight of this occurrence as \(\lambda^{i_k-i_i-k+1}\), where λ ∈ [0, 1] is a constant chosen in advance; in other words, an occurrence weighs less if characters of p are separated by other characters. Let Ï• p (a) be the sum of the weights of all occurrences of p in a, and let Ï•(a) = (Ï• p (a))p ∈ ∑∗ be an infinite-dimensional feature vector consisting of Ï• p (a) for all possible substrings p ∈ Σ*. It turns out that the dot product of two such infinite-length vectors, K(a, a′) = Ï•(a)TÏ•(a′), can be computed in time polynomial in the length of a and a′, e.g.,...

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 699.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Hardcover Book
USD 949.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2017 Springer Science+Business Media New York

About this entry

Cite this entry

(2017). String Kernel. In: Sammut, C., Webb, G.I. (eds) Encyclopedia of Machine Learning and Data Mining. Springer, Boston, MA. https://doi.org/10.1007/978-1-4899-7687-1_790

Download citation

Publish with us

Policies and ethics