An Imperfect String Matching Experience Using Deformed Fuzzy Automata

摘要

This paper presents a string matching experience using deformed fuzzy automata for the recognition of imperfect strings. We propose an algorithm based on a deformed fuzzy automaton that calculates a similarity value between strings having a non-limited number of edition errors. Different selections of the fuzzy operators for computing the deformed fuzzy automaton transitions allows to obtain different string similarity definitions. The selection of the parameters determining the deformed fuzzy automaton behavior is obtained via genetic algorithms.