We introduce a new matching criterion - function matching - that captures several different applications. The function matching problem has as its input a text T of length n over alphabet ΣT and a pattern P = P[1]P[2] ⋯ P[m] of length m over alphabet ΣP. We seek all text locations i for which, for some function f : ΣP > ΣT (f may also depend on i), the m-length substring that starts at i is equal to f(P[1])f(P[2])⋯f(P[m]). We give a randomized algorithm which, for any given constant k, solves the function matching problem in time O(n log n) with probability 1/nk of declaring a false positive. We give a deterministic algorithm whose time is O(n|ΣP|log m) and show that it is almost optimal in the newly formalized convolutions model. Finally, a variant of the third problem is solved by means of two-dimensional parameterized matching, for which we also give an efficient algorithm. © Springer-Verlag Berlin Heidelberg 2003.
CITATION STYLE
Amir, A., Aumann, Y., Cole, R., Lewenstein, M., & Porat, E. (2003). Function matching: Algorithms, applications, and a lower bound. Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2719, 929–942. https://doi.org/10.1007/3-540-45061-0_72
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