String Kernel Function: Difference between revisions
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A [[String Kernel Function]] is a [[ | A [[String Kernel Function]] is a [[kernel function]] that evaluates the similarity between two [[string]]s. | ||
* <B | * <B>AKA:</B> [[Sequence Kernel Operator]]. | ||
* <B | * <B>Context</U>:</B> | ||
** A proposed approach is to count the number of common [[Subsequence]]s between two [[string]]s and weight their matches by their [[Sequence Length]] and to computer the [[Dot Product]]. | ** A proposed approach is to count the number of common [[Subsequence]]s between two [[string]]s and weight their matches by their [[Sequence Length]] and to computer the [[Dot Product]]. | ||
** It can be a [[Bag-of-Words Kernel Function]] if a [[Unigram]] | ** It can be a [[Bag-of-Words Kernel Function]] if a [[Unigram representation]]. | ||
** It can be applied to [[Text Classification]]. | ** It can be applied to [[Text Classification]]. | ||
* <B> | ** … | ||
* <B>Counter-Example(s):</B> | |||
** a [[Tree Kernel Function]]. | |||
** a [[Matrix Kernel Function]]. | |||
* <B>See:</B> [[Convolution Kernel Function]]. | |||
---- | ---- | ||
---- | ---- | ||
=== | == References == | ||
===2002=== | === 2011 === | ||
* ([[2002_TextClassificationUsingStringKernels|Lodhi | * ([[Sammut & Webb, 2011]]) ⇒ [[Claude Sammut]], and [[Geoffrey I. Webb]]. ([[2011]]). “String Kernel.” In: ([[Sammut & Webb, 2011]]) p.929 | ||
=== 2002 === | |||
* ([[2002_TextClassificationUsingStringKernels|Lodhi et al., 2002]]) ⇒ H. Lodhi, C. Saunders, [[John Shawe Taylor]], N. Cristianini, and [[C. Watkins]]. ([[2002]]). “[http://www.jmlr.org/papers/volume2/lodhi02a/lodhi02a.pdf Text classification using string kernels].” In: The Journal of Machine Learning Research, vol:2. | |||
** Demonstrate that this kernel can be computed in linear time w.r.t to the cases and the lengths of the subsequences. | ** Demonstrate that this kernel can be computed in linear time w.r.t to the cases and the lengths of the subsequences. | ||
===2000=== | === 2000 === | ||
* ([[2000_DynamicAlignmentKernels|Watkins, 2000]]) | * ([[2000_DynamicAlignmentKernels|Watkins, 2000]]) ⇒ [[C. Watkins]]. ([[2000]]). “[http://www.svms.org/kernels/Watk99.pdf Dynamic alignment kernels].” In: A.J. Smola, P.L. Bartlett, B. Schlkopf, and D. Schuurmans, editors, Advances in Large Margin Classifiers. | ||
===1999=== | === 1999 === | ||
* ([[1999_ConvolutionKernelsOnDiscreteStructures|Haussler, 1999]]) | * ([[1999_ConvolutionKernelsOnDiscreteStructures|Haussler, 1999]]) ⇒ [[D. Haussler]]. “[http://www.cbse.ucsc.edu/staff/haussler_pubs/convolutions.pdf Convolution Kernels on Discrete Structures]." Technical Report UCSC-CLR-99-10, University of California at Santa Cruz. | ||
---- | ---- | ||
__NOTOC__ | __NOTOC__ | ||
[[Category:Concept]] | [[Category:Concept]] | ||
Latest revision as of 07:03, 8 May 2024
A String Kernel Function is a kernel function that evaluates the similarity between two strings.
- AKA: Sequence Kernel Operator.
- Context:
- A proposed approach is to count the number of common Subsequences between two strings and weight their matches by their Sequence Length and to computer the Dot Product.
- It can be a Bag-of-Words Kernel Function if a Unigram representation.
- It can be applied to Text Classification.
- …
- Counter-Example(s):
- See: Convolution Kernel Function.
References
2011
- (Sammut & Webb, 2011) ⇒ Claude Sammut, and Geoffrey I. Webb. (2011). “String Kernel.” In: (Sammut & Webb, 2011) p.929
2002
- (Lodhi et al., 2002) ⇒ H. Lodhi, C. Saunders, John Shawe Taylor, N. Cristianini, and C. Watkins. (2002). “Text classification using string kernels.” In: The Journal of Machine Learning Research, vol:2.
- Demonstrate that this kernel can be computed in linear time w.r.t to the cases and the lengths of the subsequences.
2000
- (Watkins, 2000) ⇒ C. Watkins. (2000). “Dynamic alignment kernels.” In: A.J. Smola, P.L. Bartlett, B. Schlkopf, and D. Schuurmans, editors, Advances in Large Margin Classifiers.
1999
- (Haussler, 1999) ⇒ D. Haussler. “Convolution Kernels on Discrete Structures." Technical Report UCSC-CLR-99-10, University of California at Santa Cruz.