On-Line Approximate String Matching with Bounded Errors

We introduce a new dimension to the widely studied on-line approximate string matching problem, by introducing an error threshold parameter so that the algorithm is allowed to miss occurrences with probability . This is particularly appropriate for this problem, as approximate searching is used to model many cases where exact answers are not mandatory. We show that the relaxed version of the problem allows us breaking the average-case optimal lower bound of the classical problem, achieving average case O(n log m/m) time with any = poly(k/m), where n is the text size, m the pattern length, k the number of errors for edit distance, and the alphabet size. Our experimental results show the practicality of this novel and promising research direction.

• Type: Conference
• Year: 2008
• Where: CPM
• Authors: Marcos A. Kiwi, Gonzalo Navarro, Claudio Telha
• Keywords: Combinatorics, CPM 2008, Error Threshold Parameter, Optimal Lower Bound, String Matching Problem