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  2. Word2vec - Wikipedia

    en.wikipedia.org/wiki/Word2vec

    In the continuous skip-gram architecture, the model uses the current word to predict the surrounding window of context words. [1] [2] The skip-gram architecture weighs nearby context words more heavily than more distant context words. According to the authors' note, [3] CBOW is faster while skip-gram does a better job for infrequent words.

  3. Word n-gram language model - Wikipedia

    en.wikipedia.org/wiki/Word_n-gram_language_model

    the set of 1-skip-2-grams includes all the bigrams (2-grams), and in addition the subsequences the in, rain Spain, in falls, Spain mainly, falls on, mainly the, and on plain. In skip-gram model, semantic relations between words are represented by linear combinations, capturing a form of compositionality.

  4. Skip-gram - Wikipedia

    en.wikipedia.org/?title=Skip-gram&redirect=no

    Upload file; Languages. ... Download as PDF; Printable version; From Wikipedia, the free encyclopedia. Redirect page. Redirect to: N-gram#Skip-gram ...

  5. Language model - Wikipedia

    en.wikipedia.org/wiki/Language_model

    A language model is a model of natural language. [1] Language models are useful for a variety of tasks, including speech recognition, [2] machine translation, [3] natural language generation (generating more human-like text), optical character recognition, route optimization, [4] handwriting recognition, [5] grammar induction, [6] and information retrieval.

  6. File:Skip-gram.svg - Wikipedia

    en.wikipedia.org/wiki/File:Skip-gram.svg

    You are free: to share – to copy, distribute and transmit the work; to remix – to adapt the work; Under the following conditions: attribution – You must give appropriate credit, provide a link to the license, and indicate if changes were made.

  7. Node2vec - Wikipedia

    en.wikipedia.org/wiki/Node2vec

    node2vec is an algorithm to generate vector representations of nodes on a graph. The node2vec framework learns low-dimensional representations for nodes in a graph through the use of random walks through a graph starting at a target node.