Apr 13, 2017 · Fuzzy string Matching using fuzzywuzzyR and the reticulate package in R 13 Apr 2017. I recently released an (other one) R package on CRAN - fuzzywuzzyR - which ports the fuzzywuzzy python library in R. “fuzzywuzzy does fuzzy string matching by using the Levenshtein Distance to calculate the differences between sequences (of character strings).”
The domain of Fuzzy Name Matching is not new, but with the rise of mobile and web apps, social media platforms, new messaging services, device logs and other open data formats, the nuances of data have grown, making the challenge of name matching increasingly complex.
Feb 25, 2015 · Fuzzy String Matching, also called Approximate String Matching, is the process of finding strings that approximatively match a given pattern. The closeness of a match is often measured in terms of edit distance, which is the number of primitive operations necessary to convert the string into an exact match.
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Only specialised tools that include an error-tolerant (fuzzy) matching algorithm can provide a satisfactory solution to this problem, such as DataQualityTools: You can read about how to use DataQualityTools to search for duplicates within a table in the article ' Search intelligently for duplicates and duplicate addresses with DataQualityTools '.
Mar 26, 2015 · Matching company names is indeed a serious issue. It is seen that most businessman often come up with the question how to fuzzy match company names. Numerous businessmen are there who suffers from this same kind of problem. Linking the company informations together from a disparate dataset is also important.
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