BPBM: An Algorithm for String Matching with Wildcards and Length Constraints

Authors:
Xiao-Li Hong;Xindong Wu;Xue-Gang Hu;Ying-Ling Liu;Jun Gao;Gong-Qing Wu
Affiliations:
School of Computer Science and Information Engineering, Hefei University of Technology, Hefei, China 230009;School of Computer Science and Information Engineering, Hefei University of Technology, Hefei, China 230009 and Department of Computer Science, University of Vermont, Burlington, USA 05405;School of Computer Science and Information Engineering, Hefei University of Technology, Hefei, China 230009;School of Computer Science and Information Engineering, Hefei University of Technology, Hefei, China 230009;School of Computer Science and Information Engineering, Hefei University of Technology, Hefei, China 230009;School of Computer Science and Information Engineering, Hefei University of Technology, Hefei, China 230009
Venue:
RSFDGrC '09 Proceedings of the 12th International Conference on Rough Sets, Fuzzy Sets, Data Mining and Granular Computing
Year:
2009

Citing 5
Cited 0

An algorithm for string matching with a sequence of don't cares

Information Processing Letters
Algorithms on strings, trees, and sequences: computer science and computational biology

Algorithms on strings, trees, and sequences: computer science and computational biology
A fast string searching algorithm

Communications of the ACM
Efficient pattern-matching with don't cares

SODA '02 Proceedings of the thirteenth annual ACM-SIAM symposium on Discrete algorithms
Dictionary matching and indexing with errors and don't cares

STOC '04 Proceedings of the thirty-sixth annual ACM symposium on Theory of computing

Quantified Score

Hi-index	0.00

Visualization

Abstract

Pattern matching with wildcards and length constraints under the one-off condition is a challenging topic. We propose an algorithm BPBM, based on bit parallelism and the Boyer-Moore algorithm, that outputs an occurrence of a given pattern P as soon as the pattern appears in the given sequence. The experimental results show that our BPBM algorithm has an improved time performance of over 50% with the same matching results when compared with SAIL, a state-of-the-art algorithm of this matching problem. The superiority is even more remarkable when the scale of the pattern increases.