Spelling Checker using Algorithm Damerau Levenshtein Distance and Cosine Similarity

Nur Hamidah, Novi Yusliani, Desty Rodiah

Abstract

Writing is an embodiment of the author's ideas that are to be conveyed to others. A writer often experiences typos in typing the script, so that it can influence the meaning of the text. Therefore, a system is needed to detect word errors. In this study, checking is done by using the Dictionary Lookup method and giving the candidate words using the Damerau Levenshtein Distance algorithm. Candidates will then determine the ranking by breaking the word into Bigram form and calculating the similarity value using the Cosine Similarity algorithm. The test results based on the data used yield different Mean Reciprocal Rank (MRR) values for each type of error. The type of error deletion produces an MRR value of 88.89%, the type of insertion error produces an MRR value of 97.78%, the type of substitution error produces an MRR value of 88.89%, the type of transposition error produces an MRR value of 89%

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