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Elastic-Degenerate String Matching via Fast Matrix Multiplication
[article]

Giulia Bernardini, Paweł Gawrychowski, Nadia Pisanti, Solon P. Pissis, Giovanna Rosone

2021
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arXiv
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pre-print

An elastic-degenerate (ED) string is a sequence of n sets of strings of total length N, which was recently proposed to model a set of similar sequences. The ED string matching (EDSM) problem is to find all occurrences of a pattern of length m in an ED text. An O(nm^1.5√(log m)+N)-time algorithm for EDSM is known [Aoyama et al., CPM 2018]. The standard assumption in the prior work on this question is that N is substantially larger than both n and m, and thus we would like to have a linear
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... ncy on the former. Under this assumption, the natural open problem is whether we can decrease the 1.5 exponent in the time complexity, similarly as in the related (but, to the best of our knowledge, not equivalent) word break problem [Backurs and Indyk, FOCS 2016]. Our starting point is a conditional lower bound for EDSM. We use the popular combinatorial Boolean Matrix Multiplication (BMM) conjecture stating that there is no truly subcubic combinatorial algorithm for BMM [Abboud and Williams, FOCS 2014]. By designing an appropriate reduction we show that a combinatorial algorithm solving the EDSM problem in O(nm^1.5-e+N) time, for any e>0, refutes this conjecture. Our reduction should be understood as an indication that decreasing the exponent requires fast matrix multiplication. String periodicity and fast Fourier transform are two standard tools in string algorithms. Our main technical contribution is that we successfully combine these tools with fast matrix multiplication to design a non-combinatorial Õ(nm^ω-1+N)-time algorithm for EDSM, where ω denotes the matrix multiplication exponent. To the best of our knowledge, we are the first to combine these tools. In particular, using the fact that ω<2.373 [Le Gall, ISSAC 2014; Williams, STOC 2012], we obtain an O(nm^1.373+N)-time algorithm for EDSM.

arXiv:1905.02298v3
fatcat:owglwrnjf5axbmwzqzomekd3ry