Hybrid similarity functions are combinations of token-based and character-based similarity functions. The input strings are first split into multiple smaller tokens — usually words. For more information on token-based similarity functions that apply splitting of strings, see Smith-Waterman and Smith-Waterman-Gotoh.

As a hybrid similarity, Monge-Elkan first tokenizes two strings s 1 and s 2 into tokens t i and t i, respectively. It then matches every token t i from s 1 with the token t i in s 2 that has the maximum similarity using the secondary similarity function TokenSim. The arithmetic mean over these maximum similarity scores gives the final similarity measure:

Let us consider the following input strings “Acme Soft” and “Acm Software.”

Maximum similarity for “Acme”and ”Acm” is:1 - 1/4 = 75%

1 - 4/8 = 50%

Therefore, the Monge-Elkan similarity is computed as:

This ISO specific-similarity function is based on token similarity, which is strengthened with a complex character similarity function. In comparison to Scarus similarity, Rivulatus is much more robust in verifying misspellings and handling interchanged tokens.