High Performance Computation for the Multi-Parameterized Edit Distance
Francesco Cauteruccio, Davide Consalvo, Giorgio Terracina · 2018
In this paper, we propose a method for the computation of a novel distance metrics, called Multi-Parameterized Edit Distance (MPED) among strings defined over heterogeneous alphabets. We show that the computation of MPED is hard and that several interesting application contexts can benefit from its application. We then present a novel imple- mentation strategy based on an Evolutionary Heuristics, which we experimentally demonstrate to be efficient and effective for the problem at hand. Our approach paves indeed the way to the adoption of this new metric in all those contexts in which involved strings come from heterogeneous sources, each adopting its own alphabet.