Versatile string kernels
This paper proposes a class of string kernels that can handle a variety of subsequence-based features. Slight adaptations of the basic algorithm allow for weighing subsequence lengths, restricting or soft-penalizing gap-size, character-weighing and soft-matching of characters. An easy extension of the kernels allows for comparing run-length encoded strings with a time-complexity that is independent of the length of the original strings. Such kernels have applications in image processing, computational biology; in demography and in comparing partial rankings. (C) 2013 Elsevier B.V. All rights reserved.
string kernel subsequences run-length encoding partial rankings string matching gap-penalizing soft matching