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  2. Diff-Text - Wikipedia

    en.wikipedia.org/wiki/Diff-Text

    Any similarity between the two documents above the specified minimum will be reported (if detecting moves is selected). This is the main difference between Diff-Text and most other text comparison algorithms. Diff-Text will always match up significant similarities even if contained within non-identical or moved lines.

  3. Normalized compression distance - Wikipedia

    en.wikipedia.org/wiki/Normalized_compression...

    Normalized compression distance (NCD) is a way of measuring the similarity between two objects, be it two documents, two letters, two emails, two music scores, two languages, two programs, two pictures, two systems, two genomes, to name a few. Such a measurement should not be application dependent or arbitrary.

  4. SimRank - Wikipedia

    en.wikipedia.org/wiki/SimRank

    SimRank is a general approach that exploits the object-to-object relationships found in many domains of interest. On the Web, for example, two pages are related if there are hyperlinks between them. A similar approach can be applied to scientific papers and their citations, or to any other document corpus with cross-reference information. In ...

  5. Approximate string matching - Wikipedia

    en.wikipedia.org/wiki/Approximate_string_matching

    Computing E(m, j) is very similar to computing the edit distance between two strings. In fact, we can use the Levenshtein distance computing algorithm for E ( m , j ), the only difference being that we must initialize the first row with zeros, and save the path of computation, that is, whether we used E ( i − 1, j ), E( i , j − 1) or E ( i ...

  6. Similarity measure - Wikipedia

    en.wikipedia.org/wiki/Similarity_measure

    In statistics and related fields, a similarity measure or similarity function or similarity metric is a real-valued function that quantifies the similarity between two objects. Although no single definition of a similarity exists, usually such measures are in some sense the inverse of distance metrics : they take on large values for similar ...

  7. Dice-Sørensen coefficient - Wikipedia

    en.wikipedia.org/wiki/Dice-Sørensen_coefficient

    For example, to calculate the similarity between: night nacht. We would find the set of bigrams in each word: {ni,ig,gh,ht} {na,ac,ch,ht} Each set has four elements, and the intersection of these two sets has only one element: ht. Inserting these numbers into the formula, we calculate, s = (2 · 1) / (4 + 4) = 0.25.

  8. Overlap coefficient - Wikipedia

    en.wikipedia.org/wiki/Overlap_coefficient

    The overlap coefficient, [note 1] or Szymkiewicz–Simpson coefficient, [citation needed] [3] [4] [5] is a similarity measure that measures the overlap between two finite sets.It is related to the Jaccard index and is defined as the size of the intersection divided by the size of the smaller of two sets:

  9. String metric - Wikipedia

    en.wikipedia.org/wiki/String_metric

    In mathematics and computer science, a string metric (also known as a string similarity metric or string distance function) is a metric that measures distance ("inverse similarity") between two text strings for approximate string matching or comparison and in fuzzy string searching.