A fast bit-parallel algorithm for gapped string kernels

Authors:
Chuanhuan Yin;Shengfeng Tian;Shaomin Mu
Affiliations:
School of Computer and Information Technology, Beijing Jiaotong University, Beijing, China;School of Computer and Information Technology, Beijing Jiaotong University, Beijing, China;School of Computer and Information Technology, Beijing Jiaotong University, Beijing, China
Venue:
ICONIP'06 Proceedings of the 13 international conference on Neural Information Processing - Volume Part I
Year:
2006

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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.