Uses of Interface
info.debatty.java.stringsimilarity.interfaces.NormalizedStringDistance
Packages that use NormalizedStringDistance
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Uses of NormalizedStringDistance in info.debatty.java.stringsimilarity
Classes in info.debatty.java.stringsimilarity that implement NormalizedStringDistanceModifier and TypeClassDescriptionclass
The similarity between the two strings is the cosine of the angle between these two vectors representation.class
Each input string is converted into a set of n-grams, the Jaccard index is then computed as |V1 inter V2| / |V1 union V2|.class
The Jaro–Winkler distance metric is designed and best suited for short strings such as person names, and to detect typos; it is (roughly) a variation of Damerau-Levenshtein, where the substitution of 2 close characters is considered less important then the substitution of 2 characters that a far from each other.class
Distance metric based on Longest Common Subsequence, from the notes "An LCS-based string metric" by Daniel Bakkelund.class
N-Gram Similarity as defined by Kondrak, "N-Gram Similarity and Distance", String Processing and Information Retrieval, Lecture Notes in Computer Science Volume 3772, 2005, pp 115-126.class
This distance is computed as levenshtein distance divided by the length of the longest string.class
Ratcliff/Obershelp pattern recognition The Ratcliff/Obershelp algorithm computes the similarity of two strings a the doubled number of matching characters divided by the total number of characters in the two strings.class
Similar to Jaccard index, but this time the similarity is computed as 2 * |V1 inter V2| / (|V1| + |V2|).