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  2. Normalized Google distance - Wikipedia

    en.wikipedia.org/wiki/Normalized_Google_distance

    The normalized Google distance (NGD) is a semantic similarity measure derived from the number of hits returned by the Google search engine for a given set of keywords. [1] Keywords with the same or similar meanings in a natural language sense tend to be "close" in units of normalized Google distance, while words with dissimilar meanings tend to ...

  3. Category:Statistical distance - Wikipedia

    en.wikipedia.org/wiki/Category:Statistical_distance

    Download QR code; Print/export Download as PDF; Printable version; ... Normalized compression distance; Normalized Google distance; O. Optimal matching; P.

  4. 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 ...

  5. Information distance - Wikipedia

    en.wikipedia.org/wiki/Information_Distance

    We need outside information about what the name means. Using a data base (such as the internet) and a means to search the database (such as a search engine like Google) provides this information. Every search engine on a data base that provides aggregate page counts can be used in the normalized Google distance (NGD). A python package for ...

  6. Normalized compression distance - Wikipedia

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

    Using code-word lengths obtained from the page-hit counts returned by Google from the web, we obtain a semantic distance using the NCD formula and viewing Google as a compressor useful for data mining, text comprehension, classification, and translation. The associated NCD, called the normalized Google distance (NGD) can be rewritten as

  7. Edit distance - Wikipedia

    en.wikipedia.org/wiki/Edit_distance

    LCS distance is bounded above by the sum of lengths of a pair of strings. [1]: 37 LCS distance is an upper bound on Levenshtein distance. For strings of the same length, Hamming distance is an upper bound on Levenshtein distance. [1] Regardless of cost/weights, the following property holds of all edit distances:

  8. Levenshtein distance - Wikipedia

    en.wikipedia.org/wiki/Levenshtein_distance

    Edit distance matrix for two words using cost of substitution as 1 and cost of deletion or insertion as 0.5. For example, the Levenshtein distance between "kitten" and "sitting" is 3, since the following 3 edits change one into the other, and there is no way to do it with fewer than 3 edits: kitten → sitten (substitution of "s" for "k"),

  9. Talk:Normalized Google distance - Wikipedia

    en.wikipedia.org/wiki/Talk:Normalized_Google...

    Talk: Normalized Google distance. ... Download QR code; Print/export Download as PDF; Printable version; In other projects ...