Approximate String Matching Using Deformed Fuzzy Automata: A Learning Experience
Fuzzy Optimization and Decision Making
Fuzzy location and tracking on wireless networks
Proceedings of the 4th ACM international workshop on Mobility management and wireless access
Improving folksonomies quality by syntactic tag variations grouping
Proceedings of the 2009 ACM symposium on Applied Computing
Fuzzy automata with ε-moves compute fuzzy measures between strings
Fuzzy Sets and Systems
New directions in fuzzy automata
International Journal of Approximate Reasoning
Nondeterministic fuzzy automata
Information Sciences: an International Journal
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Presents a fuzzy method for the recognition of strings of fuzzy symbols containing substitution, deletion, and insertion errors. As a preliminary step, we propose a fuzzy automaton to calculate a similarity value between strings. The adequate selection of fuzzy operations for computing the transitions of the fuzzy automaton allows us to obtain different string similarity definitions (including the Levenshtein distance). A deformed fuzzy automaton based on this fuzzy automaton is then introduced in order to handle strings of fuzzy symbols. The deformed fuzzy automaton enables the classification of such strings having an undetermined number of insertion, deletion and substitution errors. The selection of the parameters determining the deformed fuzzy automaton behavior would allow to implement recognizers adapted to different problems. The paper also presents algorithms that implement the deformed fuzzy automaton. Experimental results show good performance in correcting these kinds of errors.