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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 ...
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
NGD (normalized Google distance): (+) large vocab, because it uses any search engine (like Google); (−) can measure relatedness between whole sentences or documents but the larger the sentence or document, the more ingenuity is required (Cilibrasi & Vitanyi, 2007). [46]
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 ...
[5] [6] [7] As of 2020 his work on normalized compression distance was used in 15 US patents and on normalized Google distance in 10 US patents. Together with Ming Li he pioneered theory and applications of Kolmogorov complexity. [ 8 ]
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We can rewrite this definition in terms that explicitly highlight the information content of this metric. The set of all partitions of a set form a compact lattice where the partial order induces two operations, the meet and the join , where the maximum ¯ is the partition with only one block, i.e., all elements grouped together, and the minimum is ¯, the partition consisting of all elements ...
Nearest neighbor search (NNS), as a form of proximity search, is the optimization problem of finding the point in a given set that is closest (or most similar) to a given point.