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  2. Content similarity detection - Wikipedia

    en.wikipedia.org/wiki/Content_similarity_detection

    Systems for text similarity detection implement one of two generic detection approaches, one being external, the other being intrinsic. [5] External detection systems compare a suspicious document with a reference collection, which is a set of documents assumed to be genuine. [6]

  3. Semantic similarity - Wikipedia

    en.wikipedia.org/wiki/Semantic_similarity

    Semantic similarity is a metric defined over a set of documents or terms, where the idea of distance between items is based on the likeness of their meaning or semantic content [citation needed] as opposed to lexicographical similarity. These are mathematical tools used to estimate the strength of the semantic relationship between units of ...

  4. Dice-Sørensen coefficient - Wikipedia

    en.wikipedia.org/wiki/Dice-Sørensen_coefficient

    Other variations include the "similarity coefficient" or "index", such as Dice similarity coefficient (DSC). Common alternate spellings for Sørensen are Sorenson , Soerenson and Sörenson , and all three can also be seen with the –sen ending (the Danish letter ø is phonetically equivalent to the German/Swedish ö, which can be written as oe ...

  5. Semantic Scholar - Wikipedia

    en.wikipedia.org/wiki/Semantic_Scholar

    Semantic Scholar provides a one-sentence summary of scientific literature. One of its aims was to address the challenge of reading numerous titles and lengthy abstracts on mobile devices. [ 7 ] It also seeks to ensure that the three million scientific papers published yearly reach readers, since it is estimated that only half of this literature ...

  6. Distributional semantics - Wikipedia

    en.wikipedia.org/wiki/Distributional_semantics

    Distributional semantics favor the use of linear algebra as a computational tool and representational framework. The basic approach is to collect distributional information in high-dimensional vectors, and to define distributional/semantic similarity in terms of vector similarity. [9]

  7. Jaro–Winkler distance - Wikipedia

    en.wikipedia.org/wiki/Jaro–Winkler_distance

    The higher the Jaro–Winkler distance for two strings is, the less similar the strings are. The score is normalized such that 0 means an exact match and 1 means there is no similarity. The original paper actually defined the metric in terms of similarity, so the distance is defined as the inversion of that value (distance = 1 − similarity).

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