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  2. Word embedding - Wikipedia

    en.wikipedia.org/wiki/Word_embedding

    In natural language processing, a word embedding is a representation of a word. The embedding is used in text analysis.Typically, the representation is a real-valued vector that encodes the meaning of the word in such a way that the words that are closer in the vector space are expected to be similar in meaning. [1]

  3. Font embedding - Wikipedia

    en.wikipedia.org/wiki/Font_embedding

    Font embedding is a controversial practice because it allows copyrighted fonts to be freely distributed. The controversy can be mitigated by only embedding the characters required to view the document (subsetting). This reduces file size but prohibits adding previously unused characters to the document.

  4. Word2vec - Wikipedia

    en.wikipedia.org/wiki/Word2vec

    The idea of skip-gram is that the vector of a word should be close to the vector of each of its neighbors. The idea of CBOW is that the vector-sum of a word's neighbors should be close to the vector of the word. In the original publication, "closeness" is measured by softmax, but the framework allows other ways to measure closeness.

  5. Object Linking and Embedding - Wikipedia

    en.wikipedia.org/wiki/Object_Linking_and_Embedding

    Object Linking and Embedding (OLE) is a proprietary technology developed by Microsoft that allows embedding and linking to documents and other objects. For developers, it brought OLE Control Extension (OCX), a way to develop and use custom user interface elements.

  6. fastText - Wikipedia

    en.wikipedia.org/wiki/FastText

    fastText is a library for learning of word embeddings and text classification created by Facebook's AI Research (FAIR) lab. [3] [4] [5] [6] The model allows one to ...

  7. Bag-of-words model - Wikipedia

    en.wikipedia.org/wiki/Bag-of-words_model

    It disregards word order (and thus most of syntax or grammar) but captures multiplicity. The bag-of-words model is commonly used in methods of document classification where, for example, the (frequency of) occurrence of each word is used as a feature for training a classifier. [1] It has also been used for computer vision. [2]

  8. ELMo - Wikipedia

    en.wikipedia.org/wiki/ELMo

    ELMo (embeddings from language model) is a word embedding method for representing a sequence of words as a corresponding sequence of vectors. [1] It was created by researchers at the Allen Institute for Artificial Intelligence , [ 2 ] and University of Washington and first released in February, 2018.

  9. List of Microsoft Office filename extensions - Wikipedia

    en.wikipedia.org/wiki/List_of_Microsoft_Office...

    Pertaining file extensions include:.docx – Word document.docm – Word macro-enabled document; same as docx, but may contain macros and scripts.dotx – Word template.dotm – Word macro-enabled template; same as dotx, but may contain macros and scripts; Other formats.pdf – PDF documents.wll – Word add-in.wwl – Word add-in