{'fraction_non_alphanumeric': 0.010368663594470046, 'fraction_numerical': 0.0, 'mean_word_length': 5.076923076923077, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
Approximate Pattern Matching Using Fuzzy Logic

Pattern matching problem is still very interesting and important problem. Algorithms for the exact pattern matching search for exact patterns in some texts or figures. Algorithms for an approximate pattern matching search for exact and similar patterns with some errors. They use some measures to evaluate a similarity of found similar patterns. In the area of the pattern matching allowing errors is possible to use fuzzy logic theory. In the paper we present the algorithm for a fuzzification of a deterministic finite state automaton using a similarity function of characters. The fuzzified automaton will accept exact and similar words. The second presented algorithm is a fuzzy modification of Aho-Corasick pattern matching algorithm which still work in linear time with respect to the length of the searching text.