Abstract
In this paper, we present a new kind of gapped string kernel, named length-weighted kernels, including p-length-weighted and all-length-weighted kernels. Moreover, we propose a dynamic programming algorithm based on suffix kernel to compute the length-weighted kernels. Given strings s and t, and a gap penalty λ, all-length-weighted kernel can be calculated in time O(|s||t|) using our algorithms. Based on the relationship between all-length and p-length kernels, the p-length-weighted can be computed in O(p|s||t|) time. Furthermore, a bit-parallel technique is used to reduce the complexity from O(p|s||t|) to O(⌈pk/w⌉|s||t|), where w is the word size of the machine (e.g. 32 or 64 in practice) and k is determined by the longest matching subsequence of two strings s and t. The empirical results suggest that this bit-parallel technique algorithm combined with dynamic programming and suffix kernel technique outperforms the other approaches in some cases where the necessary condition of using bit-parallel technique can be satisfied.
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Yin, C., Tian, S., Mu, S. (2006). A Fast Bit-Parallel Algorithm for Gapped String Kernels. In: King, I., Wang, J., Chan, LW., Wang, D. (eds) Neural Information Processing. ICONIP 2006. Lecture Notes in Computer Science, vol 4232. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11893028_71
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DOI: https://doi.org/10.1007/11893028_71
Publisher Name: Springer, Berlin, Heidelberg
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