This paper revisits the problem of indexing a text S[1.,n] to support searching substrings in S that match a given pattern P[1..m] with at most k errors. A naive solution either has a worst-case matching time complexity of Ω(mk) or requires Ω(nk) space. Devising a solution with better performance has been a challenge until Cole et al. [5] showed an O(nlogk n)-space index that can support k-error matching in O(m+occ+logk n log log n) time, where occ is the number of occurrences. Motivated by the indexing of DNA, we investigate in this paper the feasibility of devising a linear-size index that still has a time complexity linear in m. In particular, we give an O(n)-apace index that supports k-error matching in O(m + occ+ (log n)k(k+1) log log n) worst-case time. Furthermore, the index can be compressed from O(n) words into O(n) bits with a slight increase in the time complexity. © Springer-Verlag Berlin Heidelberg 2006.
CITATION STYLE
Chan, H. L., Lam, T. W., Sung, W. K., Tam, S. L., & Wong, S. S. (2006). A linear size index for approximate pattern matching. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 4009 LNCS, pp. 49–59). Springer Verlag. https://doi.org/10.1007/11780441_6
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