Average-Optimal Multiple Approximate String Matching

Abstract

AbstractWe present a new algorithm for multiple approximate string matching, based on an extension of the optimal (on average) single-pattern approximate string matching algorithm of Chang and Marr. Our algorithm inherits the optimality and is also competitive in practice. We present a second algorithm that is linear time and handles higher difference ratios. We show experimentally that our algorithms are the fastest for intermediate difference ratios, an area where the only existing algorithms permitted simultaneous search for just a few patterns. Our algorithm is also resistant to the number of patterns, being effective for hundreds of patterns. Hence we fill an important gap in approximate string matching techniques, since no effective algorithms existed to search for many patterns with an intermediate difference ratio.KeywordsSearch TimeAverage CostCharacter InspectionText BlockSingle PatternThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.