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The implemented algorithms are: ‘jaro’,’jarowinkler’, ‘levenshtein’, ‘damerau_levenshtein’, ‘qgram’ or ‘cosine’.

Jaro–Winkler similarity uses a prefix scale Edit distance is usually defined as a parameterizable metric calculated with a specific set of allowed edit operations, and each operation is assigned a cost (possibly infinite).

This is further generalized by DNA sequence alignment algorithms such as the Smith–Waterman algorithm, which make an operation's cost depend on where it is applied.

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The implemented algorithms are: ‘step’, ‘linear’, ‘exp’, ‘gauss’ or ‘squared’.

The implementation is similar with numeric comparing in Elastic Search, a full-text search tool.

"Edit Distance" also known as "Levenshtein Distance "(named after the Russian scientist Vladimir Levenshtein, who devised the algorithm in 1965), is a measure of Similarity between two strings, s1 and s2. Census, is a String Comparator measure that gives values of partial agreement between two strings.

The distance is the number of insertions, deletions or substitutions required to transform s1 to s2.� The "Jaro-Winkler algorithm" is another way of calculating Edit distance between two strings. The string comparator accounts for length of strings and partially accounts for typical human errors made in alphanumeric strings.

I've developed an VBAccess code to test them prior to developing the ABAP final application.

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