The aim of this work was the behavior analysis when a spell checker was integrated\nas an extra pre-process during the first stage of the test mining. Different\nmodels were analyzed, choosing the most complete one considering\nthe pre-processes as the initial part of the text mining process. Algorithms for\nthe Spanish language were developed and adapted, as well as for the methodology\ntesting through the analysis of 2363 words. A capable notation for\nremoving special and unwanted characters was created. Execution times of\neach algorithm were analyzed to test the efficiency of the text mining\npre-process with and without orthographic revision. The total time was\nshorter with the spellchecker than without it. The key difference of this work\namong the existing related studies is the first time that the spell checker is\nused in the text mining preprocesses.
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