# Package org.apache.commons.text.similarity

package org.apache.commons.text.similarity

Provides algorithms for string similarity.

The algorithms that implement the EditDistance interface follow the same simple principle: the more similar (closer) strings are, lower is the distance. For example, the words house and hose are closer than house and trousers.

The following algorithms are available at the moment:

- `Cosine Distance`
- `Cosine Similarity`
- `Fuzzy Score`
- `Hamming Distance`
- `Jaro-Winkler Distance`
- `Jaro-Winkler Similarity`
- `Levenshtein Distance`
- `Longest Common Subsequence Distance`

The `Cosine Distance` utilises a `regular expression tokenizer (\w+)`. And the `Levenshtein Distance`'s behavior can be changed to take into consideration a maximum throughput.

Since:
  1.0

- Related Packages
  Package
  Description
  org.apache.commons.text
  Basic classes for text handling.
- Class
  Description
  CosineDistance
  Measures the cosine distance between two character sequences.
  CosineSimilarity
  Measures the Cosine similarity of two vectors of an inner product space and compares the angle between them.
  EditDistance<R>
  Interface for Edit Distances.
  EditDistanceFrom<R>
  Stores a `EditDistance` implementation and a `CharSequence` "left" string.
  FuzzyScore
  A matching algorithm that is similar to the searching algorithms implemented in editors such as Sublime Text, TextMate, Atom and others.
  HammingDistance
  The hamming distance between two strings of equal length is the number of positions at which the corresponding symbols are different.
  IntersectionResult
  Represents the intersection result between two sets.
  IntersectionSimilarity<T>
  Measures the intersection of two sets created from a pair of character sequences.
  JaccardDistance
  Measures the Jaccard distance of two sets of character sequence.
  JaccardSimilarity
  Measures the Jaccard similarity (aka Jaccard index) of two sets of character sequence.
  JaroWinklerDistance
  Measures the Jaro-Winkler distance of two character sequences.
  JaroWinklerSimilarity
  A similarity algorithm indicating the percentage of matched characters between two character sequences.
  LevenshteinDetailedDistance
  An algorithm for measuring the difference between two character sequences.
  LevenshteinDistance
  An algorithm for measuring the difference between two character sequences using the Levenshtein Distance.
  LevenshteinResults
  Container class to store Levenshtein distance between two character sequences.
  LongestCommonSubsequence
  A similarity algorithm indicating the length of the longest common subsequence between two strings.
  LongestCommonSubsequenceDistance
  An edit distance algorithm based on the length of the longest common subsequence between two strings.
  ObjectSimilarityScore<T,R>
  Scores the similarity between two `Object`s of the same type.
  SimilarityInput<E>
  An ordered input of elements used to compute a similarity score.
  SimilarityScore<R>
  Scores `CharSequence` similarity, like a `String`.
  SimilarityScoreFrom<R>
  This stores a `SimilarityScore` implementation and a `CharSequence` "left" string.