Package de.uni_trier.wi2.procake.similarity.base.string

Interface SMStringLevenshtein

  • All Superinterfaces:
    SimilarityMeasure, SMString
    All Known Implementing Classes:
    SMStringLevenshteinImpl
    public interface SMStringLevenshtein
extends SMString
    Compares two strings using the Levenshtein algorithm. The comparsion can be case sensitive or insensitive.

    Levenshtein distance (LD) is a measure of the similarity between two strings, which we will refer to as the source string (s) and the target string (t). The distance is the number of deletions, insertions, or substitutions required to transform s into t. For example,

    • If s is "test" and t is "test", then LD(s,t) = 0, because no transformations are needed. The strings are already identical.
    • If s is "test" and t is "tent", then LD(s,t) = 1, because one substitution (change "s" to "n") is sufficient to transform s into t.

    The greater the Levenshtein distance, the more different the strings are. The Worst case is O(nd)-time, average case O(n+d2)-time algorithm for edit-distance, where d is the edit-distance between the two strings.

    Levenshtein distance is named after the Russian scientist Vladimir Levenshtein, who devised the algorithm in 1965. If you can't spell or pronounce Levenshtein, the metric is also sometimes called edit distance.

    Similarity

    The similarity between s and t is defined as sim(s,t) = LD(s,t) / max(length(s),length(t))

    Online References

    Other discussions of Levenshtein distance are:

    Paper References

    • V. I. Levenshtein. Binary codes capable of correcting deletions, insertions and reversals. Doklady Akademii Nauk SSSR 163(4) p845-848, 1965, also Soviet Physics Doklady 10(8) p707-710, Feb 1966.
      Discovered the basic DPA for edit distance.
    • S. B. Needleman and C. D. Wunsch. A general method applicable to the search for similarities in the amino acid sequence of two proteins. Jrnl Molec. Biol. 48 p443-453, 1970.
      Defined a similarity score on molecular-biology sequences, with an O(n2) algorithm that is closely related to those discussed here.
    • Hirschberg (1975) presented a method of recovering an alignment (of an LCS) in O(n2) time but in only linear, O(n)-space; see [here].
    • E. Ukkonen On approximate string matching. Proc. Int. Conf. on Foundations of Comp. Theory, Springer-Verlag, LNCS 158 p487-495, 1983.
    Author:
    Rainer Maximini

    • Field Detail

      • DEFAULT_CASE_SENSITIVE

        static final boolean DEFAULT_CASE_SENSITIVE
        The default value for case sensitive is true.
        See Also:
        Constant Field Values

      • DEFAULT_THRESHOLD

        static final int DEFAULT_THRESHOLD
        The default threshold value is -1.
        See Also:
        Constant Field Values

    • Method Detail

      • isCaseInsensitive

        boolean isCaseInsensitive()

      • isCaseSensitive

        boolean isCaseSensitive()

      • setCaseInsensitive

        void setCaseInsensitive()

      • setCaseSensitive

        void setCaseSensitive()

      • getThreshold

        int getThreshold()

      • setThreshold

        void setThreshold​(int threshold)